Efficient multi-view coding using depth-map estimate and update

ABSTRACT

The unavailability of a depth map for a current picture of a reference view may be adequately addressed so as to reduce inter-view redundancies by estimating a depth map for the pictures of the reference and dependent views and updating same using motion and/or disparity data signaled within the multi-view data stream.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of copending International Application No. PCT/EP2012/072299, filed Nov. 9, 2012, which is incorporated herein by reference in its entirety, and additionally claims priority from U.S. Application No. 61/558,651, filed Nov. 11, 2011, which is also incorporated herein by reference in its entirety.

The present invention is concerned with multi-view coding in accordance with a multi-view codec.

BACKGROUND OF THE INVENTION

In multi-view video coding, two or more views of a video scene (which are simultaneously captured by multiple cameras) are coded in a single bitstream. The primary goal of multi-view video coding is to provide the end user with an advanced multimedia experience by offering a 3-d viewing impression. If two views are coded, the two reconstructed video sequences can be displayed on a conventional stereo display (with glasses). However, the usage of glasses for conventional stereo displays is often annoying for the user. Enabling a high-quality stereo viewing impression without glasses is currently an important topic in research and development. A promising technique for such autostereoscopic displays is based on lenticular lens systems. In principle, an array of cylindrical lenses is mounted on a conventional display in a way that multiple views of a video scene are displayed at the same time. Each view is displayed in a small cone, so that each eye of the user sees a different image; this effect creates the stereo impression without special glasses. However, such autosteroscopic displays involve typically 10-30 views of the same video scene (even more views may be used if the technology is improved further). More than 2 views can also be used for providing the user with the possibility to interactively select the viewpoint for a video scene. But the coding of multiple views of a video scene drastically increases the bit rate that may be used in comparison to conventional single-view (2-d) video. Typically, the bit rate that may be used increases approximately linearly way with the number of coded views. A concept for reducing the amount of transmitted data for autostereoscopic displays consists of transmitting only a small number of views (perhaps 2-5 views), but additionally transmitting so-called depth maps, which represent the depth (distance of the real world object to the camera) of the image samples for one or more views. Given a small number of coded views with corresponding depth maps, high-quality intermediate views (virtual views that lie between the coded views)—and to some extend also additional views to one or both ends of the camera array—can be created at the receiver side by a suitable rendering techniques.

For both stereo video coding and general multi-view video coding (with or without depth maps), it is important to exploit the interdependencies between the different views. Since all views represent the same video scene (from a slightly different perspective), there is a large amount of interdependencies between the multiple views. The goal for designing a highly efficient multi-view video coding system is to efficiently exploit these interdependencies. In conventional approaches for multi-view video coding, as for example in the multi-view video coding (MVC) extension of ITU-T Rec. H.264|ISO/IEC 14496-10, the only technique that exploits view interdependencies is a disparity-compensated prediction of image samples from already coded views, which is conceptually similar to the motion-compensated prediction that is used in conventional 2-d video coding. However, typically only a small subset of image samples is predicted from already coded views, since the temporal motion-compensated prediction is often more effective (the similarity between two temporally successive images is larger than the similarity between neighboring views at the same time instant). In order to further improve the effectiveness of multi-view video coding, it is useful to combine the efficient motion-compensated prediction with inter-view prediction techniques. One possibility is to re-use the motion data that are coded in one view for predicting the motion data of other views. Since all views represent the same video scene, the motion in one view is connected to the motion in other views based on the geometry of the real-world scene, which can be represented by depth maps and some camera parameters.

In state-of-the-art image and video coding, the pictures or particular sets of sample arrays for the pictures are usually decomposed into blocks, which are associated with particular coding parameters. The pictures usually consist of multiple sample arrays (luminance and chrominance). In addition, a picture may also be associated with additional auxiliary samples arrays, which may, for example, specify transparency information or depth maps. Each picture or sample array is usually decomposed into blocks. The blocks (or the corresponding blocks of sample arrays) are predicted by either inter-picture prediction or intra-picture prediction. The blocks can have different sizes and can be either quadratic or rectangular. The partitioning of a picture into blocks can be either fixed by the syntax, or it can be (at least partly) signaled inside the bitstream. Often syntax elements are transmitted that signal the subdivision for blocks of predefined sizes. Such syntax elements may specify whether and how a block is subdivided into smaller blocks and being associated coding parameters, e.g. for the purpose of prediction. For all samples of a block (or the corresponding blocks of sample arrays) the decoding of the associated coding parameters is specified in a certain way. In the example, all samples in a block are predicted using the same set of prediction parameters, such as reference indices (identifying a reference picture in the set of already coded pictures), motion parameters (specifying a measure for the movement of a blocks between a reference picture and the current picture), parameters for specifying the interpolation filter, intra prediction modes, etc. The motion parameters can be represented by displacement vectors with a horizontal and vertical component or by higher order motion parameters such as affine motion parameters consisting of six components. It is also possible that more than one set of particular prediction parameters (such as reference indices and motion parameters) are associated with a single block. In that case, for each set of these particular prediction parameters, a single intermediate prediction signal for the block (or the corresponding blocks of sample arrays) is generated, and the final prediction signal is built by a combination including superimposing the intermediate prediction signals. The corresponding weighting parameters and potentially also a constant offset (which is added to the weighted sum) can either be fixed for a picture, or a reference picture, or a set of reference pictures, or they can be included in the set of prediction parameters for the corresponding block. The difference between the original blocks (or the corresponding blocks of sample arrays) and their prediction signals, also referred to as the residual signal, is usually transformed and quantized. Often, a two-dimensional transform is applied to the residual signal (or the corresponding sample arrays for the residual block). For transform coding, the blocks (or the corresponding blocks of sample arrays), for which a particular set of prediction parameters has been used, can be further split before applying the transform. The transform blocks can be equal to or smaller than the blocks that are used for prediction. It is also possible that a transform block includes more than one of the blocks that are used for prediction. Different transform blocks can have different sizes and the transform blocks can represent quadratic or rectangular blocks. After transform, the resulting transform coefficients are quantized and so-called transform coefficient levels are obtained. The transform coefficient levels as well as the prediction parameters and, if present, the subdivision information is entropy coded.

The state-of-the-art in multi-view video coding extends the 2-d video coding techniques in a straightforward way. Conceptually, two or more video sequences, which correspond to the different views, are coded (or decoded) in parallel. Or more specifically, for each access unit (or time instant), the pictures corresponding to the different views are coded in a given view order. An MVC bitstream contains a base view, which can be decoded without any reference to other views. This ensures backwards compatibility with the underlying 2-d video coding standard/scheme. The bitstream is usually constructed in a way that the sub-bitstream corresponding to the base view (and in addition sub-bitstreams corresponding to particular subsets of the coded views) can be extracted in a simple way by discarding some packets of the entire bitstream. In order to exploit dependencies between views, pictures of already coded views of the current access unit can be used for the prediction of blocks of the current view. This prediction is often referred to as disparity-compensated prediction or inter-view prediction. It is basically identical to the motion-compensated prediction in conventional 2-d video coding; the only difference is that the reference picture represents a picture of a different view inside the current access unit (i.e., at the same time instant) and not a picture of the same view at a different time instant. For incorporating inter-view prediction in the design of the underlying 2-d video coding scheme, for each picture, one or more reference picture lists are constructed. For the base view (independently decodable view), only conventional temporal reference pictures are inserted into the reference picture lists. However, for all other views, inter-view reference pictures can be inserted into a reference picture list in addition (or instead of) temporal reference pictures. Which pictures are inserted into a reference picture list determined by the video coding standard/scheme and/or signaled inside the bitstream (e.g., in a parameter set and/or slice header). Whether a temporal or inter-view reference picture is chosen for a particular block of the current view is then signaled by coding (or inferring) a reference picture index. I.e., the inter-view reference pictures are used in exactly the same way as conventional temporal reference pictures; only the construction of the reference picture lists of slightly extended.

The current state-of-the-art in multi-view video coding is the Multi-view Video Coding (MVC) extension of ITU-T Rec. H.264|ISO/IEC JTC 1 [1][2]. MVC is a straightforward extension of ITU-T Rec. H.264|ISO/IEC JTC 1 towards multi-view video coding. Beside some extensions of the high level syntax, the only tool that has been added is the disparity-compensated prediction as described above. However, it should be noted that disparity-compensated prediction is typically only used for a small percentage of block. Except for regions that are covered or uncovered due to the motion inside a scene, the temporal motion-compensated prediction typically provides a better prediction signal than the disparity-compensated prediction, in particular if the temporal distance between the current and the reference picture is small. The overall coding efficiency could be improved if the temporal motion-compensated prediction could be combined with suitable inter-view prediction techniques. There is a conceptually similar problem in scalable video coding, where two representations of the same video sequence with different resolutions or fidelities are coded in a single bitstream. For the enhancement layer, there are in principle two possibilities to prediction a block of samples (if we ignore spatial intra prediction), using a temporal motion-compensated prediction from an already coded enhancement layer picture or an inter-layer prediction from the lower layer. In Scalable Video Coding (SVC) extension [3], the conventional temporal motion-compensated prediction has been combined with an inter-layer prediction of motion parameters. For an enhancement layer block, it provides the possibility to re-use the motion data of the co-located base layer block, but apply it to the enhancement layer (i.e., use the enhancement layer reference picture with base layer motion data). In this way, the temporal motion-compensated prediction inside a layer is efficiently combined with an inter-layer prediction of motion data. The general idea behind this technique is that all layers in a scalable bitstream show the same content, and hence also the motion inside each layer is the same. It does not necessarily mean that the best motion parameters for one layer are also the best motion parameters for a following layer due to the following effects: (1) The quantization of the reference pictures modifies the sample values and since different layers are quantized differently, the motion parameters that give the smallest distortion can be different for different layers; (2) Since the layers are coded at different bit rates, a particular set of motion parameters usually corresponds to a different trade-off between rate and distortion. And in rate-distortion optimized coding (which is for example achieved by minimizing of the Lagrangian functional D+λR of the distortion D and the associated rate R), different motion parameters can be optimal in rate-distortion sense for different layers (the operating point given by λ as well as the associated distortion or rate can be different). Nonetheless, the (optimal) motion parameters in base and enhancement layer are usually similar. And it is typically very likely that a mode the re-uses the motion parameters of the base layer (and is therefore associated with a small rate R) leads to a smaller overall cost (D+λR) than the optimal mode that is independent of the base layer. Or in other words, it is likely that the distortion increase ΔD that is associated by choosing the mode with base layer motion data instead of the mode with optimal enhancement motion data is smaller than the cost that is associated with the decrease in rate (ΔD+λΔR<0).

Conceptually, a similar concept as for SVC can also be used in multi-view video coding. The multiple cameras capture the same video scene from different perspective. However, if a real world object moves in the scene, the motion parameters in different captured views are not independent. But in contrast to scalable coding, where the position of an object is the same in all layers (a layer represent just a different resolution or a different quality of the same captured video), the interrelationship of the projected motion is more complicated and depends on several camera parameters as well as on the 3-d relationships in the real-world scene. But if all relevant camera parameters (such as focal length, distance of the cameras, and direction of the optical axis of the cameras) as well as the distance of the projected object points (depth map) are given, the motion inside a particular view can be derived based on the motion of another view. In general, for coding a video sequence or view, we don't need to know the exact motion of the object points; instead simple parameters such as motion vectors for blocks of samples are sufficient. In this spirit, also the relationship of the motion parameters between different views can be simplified to some extent.

However, favorably, the coding order in coding a multi-view signal is chosen such that the pictures conveying the texture of the respective view are coded prior to the corresponding depth map so as to be able to efficiently exploit characteristics known from coding/decoding the picture in coding/decoding the depth map. In even other words, the removal of redundancy between a depth map and the associated picture turns out to be more effective in case of a coding order which leads from the picture to the depth map rather than vice versa. Obeying this coding order, however, results in a lack of available depth map information at the decoding side at the time the decoder decodes the picture of a dependent view, since its depth map has not yet been reconstructed. Disadvantageously, coding parameters of the reference view may not be exploited efficiently. The situation is even more severe in case of multi-view data streams where depth maps of the views do not exist.

SUMMARY

According to an embodiment, an apparatus for reconstructing a multi-view signal coded into a multi-view data stream may have a dependent-view reconstructor configured to derive, for at least one of blocks of a current picture in a dependent view of the multi-view signal, a list of motion vector predictor candidates, by determining a disparity vector for the at least one block, representing a disparity between the current picture of the dependent view and a current picture of a reference view of the multi-view signal at the at least one block of the current picture of the dependent view, via motion and disparity vectors associated with a previously decoded portion of the multi-view signal; determining a block within the current picture of the reference view using the determined disparity vector; adding a motion vector to the list of motion vector predictor candidates which depends on a motion vector associated with the determined block of the picture of the reference view; and extract, for the at least one block of the current picture of the dependent view, index information specifying one motion vector predictor candidate of the list of motion vector predictor candidates, from the multi-view data stream; and reconstruct the at least one block of the current picture of the dependent view by performing a motion-compensated prediction of the at least one block of the current picture of the dependent view using a motion vector which depends on the specified motion vector candidate.

According to another embodiment, an apparatus for encoding a multi-view signal into a multi-view data stream may have a dependent-view encoder configured to derive, for at least one of blocks of a current picture in a dependent view of the multi-view signal, a list of motion vector predictor candidates, by determining a disparity vector for the at least one block, representing a disparity between the current picture of the dependent view and a current picture of a reference view of the multi-view signal at the current block of the dependent view, via motion and disparity vectors associated with a previously encoded portion of the multi-view signal; determining a block within the current picture of the reference view using the determined disparity vector; adding a motion vector to the list of motion vector predictor candidates which depends on a motion vector associated with the determined block of the picture of the reference view; and insert, for the at least one block of the current picture of the dependent view, index information specifying one motion vector predictor candidate of the list of motion vector predictor candidates, into the multi-view data stream; and encode the at least one block of the current picture of the dependent view by performing a motion-compensated prediction of the at least one block of the current picture of the dependent view using a motion vector which depends on the specified motion vector candidate.

According to another embodiment, an apparatus for reconstructing a multi-view signal coded into a multi-view data stream may have: a reference-view reconstructor configured to reconstruct a current picture of a reference view of the multi-view signal using motion compensated prediction based on motion data transmitted within the multi-view data stream for the reference view; and a depth estimator configured to estimate the depth map of the current picture of the dependent view by generating a depth map estimate of the current picture of the reference view by applying the motion data for the reference view onto a depth map estimate of a previous picture of the reference view; and warping the depth map estimate of the current picture of the reference view into the dependent view so as to acquire the depth map estimate of the current picture of the dependent view; a dependent-view reconstructor configured to reconstruct the current picture of the dependent view from a dependent view portion of the multi-view data stream using the depth map estimate of the current picture of the dependent view.

According to another embodiment, an apparatus for encoding a multi-view signal into a multi-view data stream may have: a reference-view encoder configured to encode a current picture of a reference view of the multi-view signal using motion compensated prediction based on motion data for the reference view with transmitting the motion data for the reference view via the multi-view data stream; and a depth estimator configured to estimate the depth map of the current picture of the dependent view by generating a depth map estimate of the current picture of the reference view by applying the motion data for the reference view onto a depth map estimate of a previous picture of the reference view; and warping the depth map estimate of the current picture of the reference view into the dependent view so as to acquire the depth map estimate of the current picture of the dependent view; a dependent-view encoder configured to encode the current picture of the dependent view into a dependent view portion of the multi-view data stream using the depth map estimate of the current picture of the dependent view.

According to another embodiment, a method for reconstructing a multi-view signal coded into a multi-view data stream may have the steps of: deriving, for at least one of blocks of a current picture in a dependent view of the multi-view signal, a list of motion vector predictor candidates, by determining a disparity vector for the at least one block, representing a disparity between the current picture of the dependent view and a current picture of a reference view of the multi-view signal at the at least one block of the block of the current picture of the dependent view, via motion and disparity vectors associated with a previously decoded portion of the multi-view signal; determining a block within the current picture of the reference view using the determined disparity vector; adding a motion vector to the list of motion vector predictor candidates which depends on a motion vector associated with the determined block of the picture of the reference view; and extracting, for the at least one block of the current picture of the dependent view, index information specifying one motion vector predictor candidate of the list of motion vector predictor candidates, from the multi-view data stream; and reconstructing the at least one block of the current picture of the dependent view by performing a motion-compensated prediction of the at least one block of the current picture of the dependent view using a motion vector which depends on the specified motion vector candidate.

According to another embodiment, a method for encoding a multi-view signal into a multi-view data stream may have the steps of: deriving, for at least one of blocks of a current picture in a dependent view of the multi-view signal, a list of motion vector predictor candidates, by determining a disparity vector for the at least one block, representing a disparity between the current picture of the dependent view and a current picture of a reference view of the multi-view signal at the current block of the dependent view, via motion and disparity vectors associated with a previously encoded portion of the multi-view signal; determining a block within the current picture of the reference view using the determined disparity vector; adding a motion vector to the list of motion vector predictor candidates which depends on a motion vector associated with the determined block of the picture of the reference view; and inserting, for the at least one block of the current picture of the dependent view, index information specifying one motion vector predictor candidate of the list of motion vector predictor candidates, into the multi-view data stream; and encoding the at least one block of the current picture of the dependent view by performing a motion-compensated prediction of the at least one block of the current picture of the dependent view using a motion vector which depends on the specified motion vector candidate.

According to another embodiment, a method for reconstructing a multi-view signal coded into a multi-view data stream may have the steps of: reconstructing a current picture of a reference view of the multi-view signal using motion compensated prediction based on motion data transmitted within the multi-view data stream for the reference view; and estimating the depth map of the current picture of the dependent view by generating a depth map estimate of the current picture of the reference view by applying the motion data for the reference view onto a depth map estimate of a previous picture of the reference view; and warping the depth map estimate of the current picture of the reference view into the dependent view so as to acquire the depth map estimate of the current picture of the dependent view; reconstructing the current picture of the dependent view from a dependent view portion of the multi-view data stream using the depth map estimate of the current picture of the dependent view.

According to another embodiment, a method for encoding a multi-view signal into a multi-view data stream may have the steps of: encoding a current picture of a reference view of the multi-view signal using motion compensated prediction based on motion data for the reference view with transmitting the motion data for the reference view via the multi-view data stream; and estimating the depth map of the current picture of the dependent view by generating a depth map estimate of the current picture of the reference view by applying the motion data for the reference view onto a depth map estimate of a previous picture of the reference view; and warping the depth map estimate of the current picture of the reference view into the dependent view so as to acquire the depth map estimate of the current picture of the dependent view; encoding the current picture of the dependent view into a dependent view portion of the multi-view data stream using the depth map estimate of the current picture of the dependent view.

According to another embodiment, a computer program may have a program code for performing, when running on a computer, a method according to claim 18.

According to another embodiment, a computer program may have a program code for performing, when running on a computer, a method according to claim 20.

In accordance with a first aspect of the present invention, an idea is exploited according to which the missing of a depth map for a current picture of a reference view—due to the transmission thereof being not anticipated anyway, or due to the advantageous coding order between a texture/picture and its depth map, or due an anticipated discarding of depth data from the bitstream during transmission or decoding—may be adequately addressed so as to reduce inter-view redundancies by estimating a depth map for the pictures of the reference and dependent views and updating same using motion and/or disparity data signaled within the multi-view data stream. In particular, virtually all multi-view data streams have random access points defined therein, i.e. time instances corresponding to pictures of the views of the multi-view signal which are coded without temporal prediction and other dependencies to previously coded pictures, but merely using intra prediction as far as the reference view is concerned, and intra prediction as well as disparity-based prediction as far as the dependent view is concerned. Accordingly, the disparity data signaled within the multi-view data stream for inter-view prediction may be exploited to initialize a depth map estimate for the dependent view, and this primary depth map estimate may be consecutively updated during the further course of the multi-view coding using motion data and/or disparity data signal within the multi-view data stream. The thus obtained depth map estimate continuously updated, enables the dependent various methods of inter-view redundancy reduction to be performed in a more efficient way than without having access to this depth map estimate.

According to another aspect, the following discovery is exploited: the overhead associated with an enlarged list of motion predictor candidates for a block of a picture of a dependent view is comparatively low compared to a gain in motion vector prediction quality resulting from an adding of a motion vector candidate which is determined from an, in disparity-compensated sense, co-located block of a reference view. The disparity between both blocks may or may not be determined using the first aspect.

BRIEF DESCRIPTION OF THE DRAWINGS

Embodiments of the present invention will be detailed subsequently referring to the appended drawings, in which:

FIG. 1 shows a block diagram of an apparatus for reconstruction of a multi-view signal in accordance with an embodiment;

FIG. 2 shows a block diagram of an apparatus for encoding a multi-view signal fitting to the apparatus of FIG. 1 in accordance with an embodiment;

FIG. 3 shows a general relationship between projected objects points, temporal motion vectors, and disparity vectors in the pictures of different views and time instances;

FIG. 4 shows a basic process for deriving a motion vector for the current block given the motion in a reference view and a depth map estimate for the current picture (using a particular sample position inside the current block);

FIG. 5 shows a basic process for mapping a depth map given for one view to another view: (left) given depth map for a view, where the grey area represents a background and white area represents a foreground object; (middle) converted depth map obtained by displacing the samples with the disparity vectors that corresponds to the depth values and keeping the foreground object for locations to which more than one sample is projected, the black area represents on disoccluded area to which no sample has been projected; (right) converted depth map after filling the disoccluded areas by the depth value for the background;

FIG. 6 shows a generation of depth maps (using disparity vectors) for a random access unit;

FIG. 7 shows temporal prediction of an estimated depth map using the motion parameters coded in the base view; and

FIG. 8 shows an update of the depth map using actually coded motion and disparity vectors.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 shows an embodiment for an apparatus 10 for reconstructing a multi-view signal 12 coded into a multi-view data stream 14. The apparatus 10 comprises an input 16 for the multi-view data stream 14, and two outputs 18 a and 18 b for a reference view signal 20 and a dependent view signal 22, respectively.

Further, apparatus 10 comprises a reference view reconstructor 24 connected between input 16 and output 18 a and a dependent view reconstructor 26 connected between input 16 and output 18 b. A depth map estimator 28 of apparatus 10 is connected between a parameter output of reference view reconstructor 24 and a reference input of dependent view reconstructor 26, and to a parameter output of dependent view reconstructor 26.

As will be outlined in more detail below, the apparatus or decoder 10 of FIG. 1 reconstructs the multi-view signal 12 from the multi-view data stream 14 by obeying a coding/decoding order according to which the reference signal 20 is processed prior to dependent view 22. The multi-view signal 12 may, as shown in FIG. 1, not only represent a spatial sampling of one common scene from different view directions or view points associated with respective views 20 and 22, but also a temporal sampling of this scene as it is illustrated in FIG. 1 exemplarily by showing three time instants T−1, T and T+1 along a time axis 30. For each time instant, each view 20 and 22 comprises a picture 32 t ₁ and 32 t ₂, wherein each picture 32 t _(1,2) represents a respective texture map.

It is noted that FIG. 1 assumes that both views 20 and 21 have their pictures 32 t _(1,2) temporally aligned. However, the time resolution between view 20 and view 22 may differ. Naturally, the same applies to the spatial resolution of the pictures and depth maps.

Moreover, decoder 10 is configured to process the multi-view signal 12 sequentially in time. To be more precise, decoder 10 is configured to reconstruct the pictures 32 t _(1,2) of a certain time instance, such as T−1, prior to continuing with processing the pictures and depth maps of the subsequent time instance T. In this regard, it is noted that the temporal coding order among the time instances of the multi-view signal 12 may be equal to the presentation time order of the pictures and depth maps, respectively, or may differ therefrom.

The reference view reconstructor 24 is configured to reconstruct the reference view 20 from a reference view portion 36 of the multi-view data stream 14, while the dependent view reconstructor 26 is configured to reconstruct the dependent view 22 based on a dependent view portion 38 of the multi-view data stream 14. In fact, reference view reconstructor 24 and dependent view reconstructor 26 may be configured to operate in a similar manner. For example, reference reconstructor 24 and dependent view reconstructor 26 may operate on a block-wise basis. Both may, for example, be configured as a hybrid video decoder, respectively. The reference view reconstructor 24 reconstructs, for example, the picture 32 t ₁ of a current time instant T by assigning a respective one of available coding modes to the blocks 40 into which this picture is subdivided. The subdivision of picture 32 t ₁ into blocks may be predefined by default or may be signaled within the multi-view data stream 14. The subdivision may subdivide picture 32 t ₁ in a regular manner into blocks of the same size or blocks of different size. Even further, a multi-tree subdivisioning may be possible so that the block size of blocks 40 may be locally adapted to the picture content. The coding modes available may comprise one or more intra prediction modes according to which reference view reconstructor 24 fills the respective block 40 by prediction from already reconstructed samples of already reconstructed blocks preceding the current block in a decoding order defined among the blocks of picture 32 t ₁, one or more inter prediction modes according to which reference view reconstructor 24 reconstructs the respective block by motion compensated and/or prediction using motion data such as motion vectors, reference picture indices and the like. For example, for illustration purposes two blocks are exemplarily shown to be reconstructed by inter prediction. The motion data 42 for these inter-predicted blocks may comprise motion vectors used by reference view reconstructor 24 to copy respective portions of a reconstructed version of a reference picture 32 t ₁ indexed by a motion reference index also comprised by the motion data 42. The motion data 42 is comprised by the reference view portion 36 of multi-view data stream 14.

The dependent view reconstructor 26 operates quite the same as reference view reconstructor 24 with dependent view reconstructor 26, however, being configured to reconstruct the dependent view 22 from the dependent view portion 38. Accordingly, in reconstructing a current picture 32 t ₂ of current time instant T, dependent view reconstructor 26 may also use a block-wise processing using a subdivision into blocks 50 which may be fixed or signaled within multi-view data stream 14. Alternatively, depth map based inter-view prediction of the subdivision into blocks 50 as outlined in more detail below may be used by dependent view reconstructor 26 so as to derive the subdivision into blocks 50 for view 22 from the subdivision into blocks 40 of view 20. As far as the coding modes are concerned, dependent view reconstructor 26 may support coding modes as they have been described with respect to the reference view reconstructor 24. Accordingly, illustratively, two blocks 50 are exemplarily shown to be subject to inter prediction using motion data 54, respectively, so as to be appropriately copied from respective portions of a reconstructed version of previously reconstructed pictures 32 t ₂, respectively. Together, this motion data 58 represents the motion data for the current picture or current time instance of view 22. In addition to these coding modes, however, dependent view reconstructor 26 has the ability to support one or more inter-view prediction modes for using disparity-compensated prediction in order to copy respective blocks from portions of view 20 of the same time instance, but spatially displaced, as defined by some disparity data. In FIG. 1, one disparity predicted block in picture 32 t ₂ is exemplarily shown along with the corresponding disparity data 60. Disparity data 60 may, for example, comprise a disparity vector or at least a disparity component along the view offset direction between views 20 and 22, and optionally a view index indicating the reference view from which the respective block 50 of the dependent view 22 depends, which index may be favorable in case of the coexistence of more than two views as exemplarily shown in FIG. 1.

That is, reference view reconstructor 24 and dependent view reconstructor 26 operate in a manner so as to reduce the redundancies along the time axis 30 and in inter-view direction, between views 20 and 22, as far as possible. This is also true, for example, for the prediction of the side information such as the motion data and disparity data as well as the coding modes and the subdivision information mentioned above. All of this information shows redundancies among each other in time direction, and between the views.

However, the dependent view reconstructor 26 could more efficiently exploit the redundancy between views 20 and 22 if the dependent view reconstructor 26 had access to a depth map for a currently decoded picture 32 t ₂. Accordingly, the depth estimator 28 is configured to provide a depth map estimate 64 as an estimate for a depth map of the current picture 32 t ₂ of the current time instant T in the manner described in more detail below, and the dependent view reconstructor 26 is configured to reconstruct the current picture 32 t ₂ of the current time instant of the dependent view 22 from the dependent view portion 38 of the multi-view data stream 14 using this depth map estimate 64. For example, having the depth map estimate 64 at hand, the dependent view reconstructor 26 is able to predict the motion data 54 of the current picture of the dependent view 22 based on the depth map estimate 64 of the current view 22 and the motion data 42 for the current picture of the reference view 20 and reconstruct the current picture of the dependent view 22 using motion compensated prediction based on the predicted motion data. For example, the current-view reconstructor 24 may be configured to, in predicting the motion data 54, use the depth data estimate 64 of the dependent view 22 to locate corresponding positions in the current picture of the reference view 20 and use the motion data 42 for the current picture of the reference view 20 at the corresponding positions to predict the motion data 54 of the current picture of the dependent view 22. In the following description, a possible way how the spatial look-up using the depth data estimate 64 is done is described in more detail below. In particular, in the following description, the fact that the motion data 42 forms a good predictor for the motion data 54 is motivated in more detail. Naturally, refinement data in order to signal a prediction residual for the motion data 54 may be comprised by the dependent view portion 38. In particular, as will be set out in more detail below, dependent view reconstructor 26 may be configured to apply disparity vectors derived from the depth data estimate 64 for one or more predetermined sample positions within a current block 50 of picture 32 t ₂ of the current time instant of dependent view 22 and use these disparity vectors in order to locate corresponding or warped positions in picture 32 t ₁ of the same time instant of view 20 with using the motion data 42 of the one or more blocks 40 containing the one or more warped positions as a predictor for the motion data 54 of the current block 50. In case of more than one such reference sample position within the current block 50, the mean or median value of the resulting one or more reference motion data of the targeted block or blocks 40 may be used as the predictor.

Further, the dependent view reconstructor 26 could be configured to predict the disparity data 60 for the current picture of the dependent view 22 based on the depth data estimate 64 of the dependent view 22 and reconstruct the current picture of the dependent view 22 using disparity compensated prediction based on the predicted current disparity data. Again, refinement may be signaled within dependent view portion 38 of the multi-view data stream 14 and used by dependent view reconstructor 26 to refine the predicted current disparity data. Further, as outlined above, theoretically the disparity data 60 of blocks 50 could be predicted too in the same way. As will be outlined in more detail below, the dependent view reconstructor 26 could be configured to predict the disparity data 60 and 62 based on the depth data estimate 64 of the current view by converting the depth data into disparity vectors and using these disparity vectors as a predictor for the disparity vectors within the disparity data 60 and 62, respectively, directly.

Naturally, dependent view reconstructor 26 could support any combination of the just-mentioned possibilities so as to use the depth data estimate so as to reduce the inter-view redundancy between views 20 and 22.

In order to derive the just-mentioned depth data estimate 64, the depth estimator 28 acts as follows.

In particular, in accordance with the embodiment of FIG. 1, the depth estimator 28 ensures that each picture 32 t _(1,2) has an depth map estimate 64 associated therewith which are consecutively derived from each other in a chain of updates. As will be outlined in more detail below, depth estimator 28 is configured to continuously update the depth map estimates 64 in a ping pong manner between views 20 and 22 primarily with the aim to provide each picture 32 t ₂ of dependent view 22 with such a depth map estimate 64 in order to serve as a basis for the above-outlined improved inter-view redundancy reduction.

Preliminarily, it is assumed that depth estimator 28 already has access to such a depth estimate for one or more previous pictures 32 t ₁ of the reference view 20 such as time instance T−1. A way how depth estimator 28 could have gained access to this depth map estimate 74 for the previously decoded picture 32 t ₁ of the reference view 20 is described further below. It should be noted, however, that such depth map data could be intermittently signaled explicitly within the multi-view data stream 14 for first pictures 32 t ₁ of the reference view 20 within so called random access units, i.e. groups of pictures 32 t ₁ which are decodable without reference to any previous portions of signal 12. In order to illustrate this possibility, a dashed line connects depth estimator 28 with input 16. In the following description, a possibility is presented where the extra transmission of such starting depth map is not necessary. Rather, the disparity data within the data stream portion 38 for the first picture 32 t ₂ of the dependent view 22 in coding order within the random access unit is exploited to construct the starting depth map of the first picture 32 t ₁ of the reference view 20 in coding order within the random access unit.

In particular, the depth estimator 28 is configured to generate the depth map 64 of the current picture 32 t ₂ of the dependent view 22 by applying the motion data 42 for the current picture 32 t ₁ of the reference view 20 at the current time instance T onto the depth map estimate 74 of any previous picture 32 t ₁ of the reference view 20 at the time instant T−1, for example. As already noted above, the reference-view reconstructor 24 reconstructs the current picture 32 t ₁ of the reference view 20 using motion compensated prediction based on the motion data 42, which is signaled within the multi-view data stream 14 for the reference view 20. The depth estimator 28 has access to this motion data 42 and uses this motion data 42 for one of the mentioned updates of the chain of updates, namely the transition 71 from the depth map estimate 74 of the reference picture 32 t ₁ at the previous time instant T−1 to the depth map estimate 64 of the current picture 32 t ₁ at the current time instant T. A way how this may be performed will be outlined in more detail below. Preliminarily, it shall be sufficient to note that applying 71 the motion data 42 onto the depth map 74 for the previous time instance T−1 could mean that co-located blocks 72, i.e. portions within depth map estimate 64 of the current picture 32 t ₁ which are co-located to blocks 40 for which this motion data 42 has been signaled in the stream portion 36, are updated with, i.e. copied from, content of the referenced depth map estimate, i.e. the depth map estimate 74 for the picture 32 t ₁ of the previous time instance T−1 at portions within the referenced depth map estimate 74 pointed to by the motion data 42′ equal to motion data 42. Remaining holes may be filled by interpolation and/or extrapolation exploiting additional information offered by the intra-coded blocks among block 40 of the current picture 32 t ₁. As a result, the depth map estimate 64 has been updated (or generated by transitioning from T−1 to T).

Again, depth estimator 28 performs this update/transition 71 merely in order to prosecute further the chain of updates described further below so as to serve as a basis for deriving the depth map estimate 64 of the current picture 32 t ₂ of the dependent view 22 of the same time instants T. To finalize the derivation, depth estimator 28 warps the updated depth map estimate 64 of the current picture 32 t ₁ of the reference view 20 into the dependent view 22 so as to obtain the depth map estimate 64 of the current picture 32 t ₂ of the dependent view 22. That is, as the motion data 42 is defined merely at a block granularity, the update/transition 71 and the resulting depth map estimate 64 of view 22 as resulting from the warping 78 represent a quite coarse estimation of the depth, but as will be shown below such a coarse estimate is sufficient in order to significantly increase the efficiency in performing the inter-view redundancy reduction.

Although possible details regarding the warping 76 are also described further below, briefly spoken, the dependent-view reconstructor 26 may be configured to perform the warping 78 by deriving disparity vectors from the depth map estimate 64 of current picture 32 t ₁ and applying the derived disparity vectors onto the depth map estimate 64 itself, so as to obtain the warped depth map estimate 64 of the current picture 32 t ₂ of the dependent view 22.

Thus, as soon as depth estimator 28 has provided dependent-view reconstructor 26 with the result of the warping 76, namely the depth map estimate 64 of the current time instant T for view 22, dependent view reconstructor 26 is able to use this depth map estimate 64 for performing the above-outlined inter-view redundancy reduction for which possible implementations are set out in more detail below.

However, depth estimator 28 continues to update 77 this depth map estimate 64 so as to obtain an updated depth map estimate 74 for the current picture 32 t ₂ of the reference view 22 and thereby maintaining the chain of updates leading to the estimate for the next time instance T+1. Accordingly, the dependent-view reconstructor 26 is configured to update 77 the depth map estimate 64 of the current picture 32 t ₂ of the dependent view 22 of the current time instance T using the disparity and/or motion data 54 and 60 for the dependent view 22 in a manner similar, at least for the motion data 54, as described above with respect to the update step 71. That is, the dependent view reconstructor 26 uses the disparity/motion data for the picture 32 t ₂ for time instance T within stream portion 38 for reconstructing this picture 32 t ₂. As far as the disparity data 60 is concerned, depth estimator 28 may easily convert the disparity vectors contained within the disparity data 54 into depth values and assign, based on these depth values, updated depth values to samples of the updated depth map estimate 79 b of the current picture 32 t ₂ of the dependent view 22 which are co-located to the respective disparity-predicted block 50 in picture 32 t ₂. The motion data 54 could be used so as to copy content of the depth map estimate 74 of the picture 32 t ₂ of a referenced previous time instance T−1 of the dependent view 22, at portions thereof pointed to by motion data equal to motion data 54, into portions within the updated depth map estimate 74 of the current picture 32 t ₂ which are co-located to blocks 50 for which this motion data 42 has been signaled in the stream portion 36. Remaining holes may be filled by interpolation and/or extrapolation exploiting additional information offered by the intra-coded blocks among block 40 of the current picture 32 t ₁. As a result, the updated depth map estimate 74 of the current picture 32 t ₂ has been updated (or generated by transitioning from T−1 to T). A possibility for as to how the depth map estimate 74 of the picture 32 t ₂ of a referenced previous time instance T−1 of the dependent view 22 may have been derived at the beginning of an random access unit, is described further below. However, the above mentioned possibly explicitly transmitted depth map for view 20 at the beginning of such random access unit may be warped to view 22 to obtain the depth map estimate 74 of the picture 32 t ₂ of a referenced previous time instance T−1 of the dependent view 22, alternatively.

In order to reduce blocking artifacts, the updates 71 and 77 could be performed by using weighting functions reducing the influence of the updates of the individual blocks at the block borders.

That is, on the basis of the depth map estimate 64 as obtained by warping 76, the dependent-view reconstructor 26 reconstructs the current picture 32 t ₂ of dependent view 22 using disparity and/or motion compensated prediction based on the disparity and/or motion data 54 and 60 for the dependent view 22 comprised by the dependent view portion 38 of the multi-view data stream 14, and in doing so, the dependent-view reconstructor 26 provides the depth estimator 28 with the disparity and/or motion data 54, 60, then used by depth estimator 68 to perform update 77.

After this update 77, the depth estimator 28 is able to warp-back 78 the updated depth map estimate 74 of the current picture 32 t ₂ of the dependent view 22 into the reference view 20 so as to obtain the updated depth map estimate 74 of current picture 32 t ₁ of the reference view 20 for a time instance T which may then serve as a basis/reference for the transition/update 79 to the next time instance T+1 and so forth.

From that time on, depth estimator 28 merely repeats processes 71, 76, 77 and 78 iteratively (wherein step 79 corresponds to step 71) so as to model the depth map estimate along the time axis 30 so as to continuously support the dependent view reconstructor 26 with the depth map estimate 64.

Further details regarding all these steps 71, 76, 77, 78, and 79 are described in further detail below. All of these further details shall be individually applicable to the description brought forward with regard to FIG. 1.

Before describing further details regarding the concepts outlined above, an embodiment for an encoder fitting to the decoder of FIG. 1 is described with respect to FIG. 2. FIG. 2 shows an apparatus for encoding the multi-view signal 12 into the multi-view data stream 14 and comprises, to this end, a reference view encoder 80, a dependent view encoder 82 and a depth estimator 84 with the encoder generally indicated with reference sign 90. The reference view encoder 80 is configured to encode the reference view 20 of the multi-view signal 12 into the reference view portion 36 of the data stream 14, while dependent view encoder 82 is responsible for encoding the dependent view 22 of multi-view signal 12 into the dependent view portion 38 of the multi-view data stream 14. Reference view encoder 80 and dependent view encoder 82 may operate in a backward predictive manner and the depth estimator 84 may be configured to perform the depth map estimate and its continuous update in the manner described above with respect to the decoder 10 by using the same information available from reference view encoder 80 and dependent-view encoder 82. That is, the depth estimator 84 is configured to generate 71 a depth map estimate 64 of the current picture 32 t ₂ of the dependent view 22 by applying motion data 42 for the reference view having been used to motion compensatedly predict the current picture of the reference view, onto a depth map estimate of a previous picture 32 t ₁ of the reference view 20 and warping 76 the thus obtained depth map estimate 64 of the current picture 32 t ₁ of the reference view 20 into the dependent view 22 so as to obtain the depth map estimate 64 of the current picture 32 t ₂ of the dependent view 22. Likewise, depth estimator 84 also performs the subsequent update step 77 and the following back-warp step 78. To this end, reference view encoder 80 and dependent view encoder 82 may be parallely connected between an input and an output of encoder 90, while depth estimator 84 may be connected between a parameter output of reference view encoder 80 and a reference input of dependent view encoder 82 and connected to a parameter output of dependent view encoder 82. The reconstruction output of reference view encoder 80 may be connected to an prediction parameter output of reference view encoder 80 such as an output of an internal prediction block.

The dependent-view encoder 82 may encode the current picture or current time instant of the dependent view 22 using the depth map estimate 64 in the manner outlined above with respect to FIG. 1, namely for predicting motion data 58 or at least 54, or predicting disparity data 60 and 62 or at least 60, or at least a part of these options, and with or without generating prediction residual data for the respective motion or disparity data, so as to form a part of the dependent view portion 38.

In the following, more detailed embodiments are presented, which are especially advantageous when combined with hybrid coding types using block merging, multi-tree block partitioning of regularly arranged tree-root blocks such as in HEVC.

The state-of-the art concepts for employing motion data of a reference view for efficiently coding a further view have all been developed based on the MVC extension of ITU-T Rec. H.264|ISO/IEC 14496-10. The new video coding standardization project of the ITU-T and ISO/IEC JTC 1/WG 11, which is also referred to as HEVC, shows very promising improvements in conventional 2-d video coding technology. The current working draft of HEVC provides substantial coding gains compared to ITU-T Rec. H.264|ISO/IEC 14496-10. For achieving these gains several concepts have been extended in comparison to ITU-T Rec. H.264|ISO/IEC 14496-10. The main improvements in the area of motion parameter coding and motion-compensated prediction include the following:

-   -   While the blocks sizes that are used for motion-compensated         prediction in ITU-T Rec. H.264|ISO/IEC 14496-10 range from 4×4         to 16×16 luma samples, a much larger variety of blocks sizes is         supported in HEVC, which ranges from 4×4 to 64×64 luma samples.         In addition, the basic coding units are not given by fixed         macroblock and sub-macroblocks, but are adaptively chosen. The         largest coding unit is typically a block of 64×64 luma samples,         but the largest block size can actually be signaled inside the         bitstream. The splitting of a block into subblock can establish         a subdivision hierarchy of 4 or more levels.     -   Motion vectors are not coded by using a fixed motion vector         predictor. Instead there exists a list of motion vector         predictor candidates, and one of these predictors is adaptively         chosen on a block basis. The chosen predictor is signaled inside         the bitstream.     -   ITU-T Rec. H.264|ISO/IEC 14496-10 provides the SKIP and DIRECT         for which the motion parameters (number of hypothesis, reference         indices, motion vectors) are completely derived from already         coded information, without coding any additional parameters         (except residual information). HEVC provides a so-called merge         mode. For this mode a list of motion parameter candidates given         by the motion parameters of spatially and temporally neighboring         blocks is established. The motion parameters (including the         number of hypothesis, reference indices, and motion vectors)         that are chosen for a block coded in the merge mode are signaled         by transmitting an index into the candidate list.

The following description will describe a concept for employing the motion data of already coded views as well as the disparity data for already coded pictures of a current view for coding a current picture of the current view in multiview video coding, with this concept representing a possible implementation of the embodiment described above. Further, the advantages resulting from the above and following embodiments will be explained in more detail. By employing the already coded motion and disparity information for predicting the temporal motion (or the disparity) of the current view, the motion data rate for the current view can be significantly reduced, which results in an overall bit rate saving for the coding of multiview video sequences. The described concept provides the possibility to directly derive all motion data for a block (or a general set of samples), in which case no further motion information are transmitted for a block. And it also provides the possibility to derive a motion vector predictor that is added to a list of candidate motion vector predictors. For the latter possibility, an index into the list of motion vector predictors as well as a motion vector difference are transmitted for a block, which specify the final motion vector used for motion-compensated prediction. In a particular embodiment of the invention, not only the motion parameters for a block, but also the partitioning information for the block (which can split the block into smaller blocks and assign separate motion parameters to each sub-block) can be derived based on the already coded motion and disparity information. The concept is applicable to general block-based hybrid coding approaches without assuming any particular macroblock or sub-macroblock structure. The general block-based motion compensation is not modified, but only the coding of motion parameters, so that the concept can be integrated in general block-based hybrid video coding schemes with a very small complexity increase. It can also be straightforwardly extended to more general concepts, in which not rectangular blocks but other sets of samples are associated for unique motion parameters. The concept is applicable to multiview coding with and without additional depth maps. The disparity information for calculating the motion parameters can be derived based on coded depth maps based on coded disparity vectors.

The following description will describe a concept for employing the motion data of already coded views as well as the disparity data for already coded pictures of a current view for coding a current picture of the current view in multiview video coding, with this concept representing a possible implementation of the embodiment described above. Further, the advantages resulting from the above and following embodiments will be explained in more detail. By employing the already coded motion and disparity information for predicting the temporal motion (or the disparity) of the current view, the motion data rate for the current view can be significantly reduced, which results in an overall bit rate saving for the coding of multiview video sequences. The invention provides the possibility to directly derive all motion data for a block (or a general set of samples), in which case no further motion information are transmitted for a block. And it also provides the possibility to derive a motion vector predictor that is added to a list of candidate motion vector predictors. For the latter possibility, an index into the list of motion vector predictors as well as a motion vector difference are transmitted for a block, which specify the final motion vector used for motion-compensated prediction. In a particular embodiment of the invention, not only the motion parameters for a block, but also the partitioning information for the block (which can split the block into smaller blocks and assign separate motion parameters to each sub-block) can be derived based on the already coded motion and disparity information. The concept is applicable to general block-based hybrid coding approaches without assuming any particular macroblock or sub-macroblock structure. The general block-based motion compensation is not modified, but only the coding of motion parameters, so that the concept can be integrated in general block-based hybrid video coding schemes with a very small complexity increase. It can also be straightforwardly extended to more general concepts, in which not rectangular blocks but other sets of samples are associated for unique motion parameters. The concept is applicable to multiview coding with additional depth maps. The disparity information for calculating the motion parameters can be derived based on coded depth maps.

One advantage of the concept presented now compared to conventional techniques for employing the motion data of already coded views is that the motion/disparity predictors are completely derived based on coded motion and disparity/depth information, without assuming any particular structure of the disparity field. At no point, it is not assumed that the disparity field can be well approximated by constant translational or affine parameters for an image; instead actually coded disparity information are used for accessing the motion of an already coded view. Further, it is not assumed that the disparity of a macroblock is similar to the disparity of neighboring blocks which assumption is unsecure. By using actually coded depth/disparity information, the concept provides suitable disparity estimates for blocks at object boundaries. Further, since no assumption that the motion of the current block is similar to that of neighboring blocks; is made, improved motion parameter predictors at object boundaries are provided. Furthermore, the concept does not require any transmission of disparity corrections. further, the concept does not require modifying the actual motion/disparity compensation process of hybrid video coding designs for being built into same. Only the derivation of motion parameters and/or motion parameter predictors is changed, so that it can be included in conventional video coding designs without any big modification and has a small complexity. In addition it should be noted that the concept is applicable to the coding with and without depth maps. Depth maps need not to be coded as part of the bitstream. Rather, coded disparity vectors may be used for deriving disparities. The concept described hereinafter can be decomposed into the following steps:

-   -   Derivation of depth/disparity data for the current picture of         the current view.     -   Derivation of candidate motion or disparity data for a current         block based on the derived depth/disparity data.     -   Coding of the motion or disparity data for a current block.

In the following, these steps including advantageous embodiments are described in more detail. All steps are described for block-based motion compensation with translational motion vectors. The concept is, however, also applicable to more general schemes in which a generalized set of samples (e.g., a non-rectangular part of a block, or any other shape) is associated with a unique set of motion parameters; and it is also applicable for coding schemes in which the motion compensation is carried out using higher order motion models (e.g., affine motion models, or other N-parameter motion models).

Before describing the details of the concept, we briefly describe the advantage and underlying thoughts also valid for the above, more generic embodiment. The basic relationship between the projection of a real-world object point in different views and at different time instances in illustrated in FIG. 3. Assuming we know the real motion inside the views and the real disparities between views, the corresponding motion and disparity vectors are given as follows:

-   -   the motion vector for the current view is given by the         difference of the locations of the projected object point in the         reference picture of the current view and the current picture of         the current view, MV_(C)(x_(C,t))=x_(C,t−1)−x_(C,t)     -   the motion vector for the reference view is given by the         difference of the locations of the projected object point in the         reference picture of the reference view and the current picture         of the reference view, MV_(R)(x_(R,t))=x_(R,t−1)−x_(R,t)     -   the disparity vector for the current time instant is given by         the difference of the locations of the projected object point in         the current picture of the reference view and the current         picture of the current view, DV_(t)(x_(C,t))=x_(R,t)−x_(C,t)     -   the disparity vector for the reference time instant is given by         the difference of the locations of the projected object point in         the reference picture of the reference view and the reference         picture of the current view,         DV_(t−1)(x_(C,t−1))=x_(R,t−1)−x_(C,t−1)

Hence, we have the following relationship between the motion and disparity vectors: MV_(C)(x _(C,t))+DV_(t−1)(x _(C,t−1))−MV_(R)(x _(R,t))−DV_(t)(x _(C,t))=0

If three of the motion and disparity vectors are given, the fourth vector can be calculated by a simple addition. In particular, the temporal motion vector for the current view can be derived according to MV_(C)(x _(C,t))+MV_(R)(x _(R,t))+DV_(t)(x _(C,t))−DV_(t−1)(x _(C,t−1)) if the motion vector of the same object point in the reference picture as well as the disparity vectors at both time instants are given. In most cases, the motion vector (or motion parameters) for the reference view are given, because this view is already coded using motion-compensated prediction. But the disparities are usually not given, they can only be estimated. However, by using two estimated values the accuracy of the final results may be quite inaccurate and not suitable for deriving sufficiently accurate temporal motion vector predictors. But in general, it is justified to assume that the depth an object point (distance of the real-world object point from the camera) is nearly constant between the time instances corresponding to the current and the reference picture (the object motion from or to the camera between two successive pictures is usually much smaller than the distance of the object to the camera). Then, also the disparities are nearly constant and the relationship between the motion vectors simplifies to MV_(C)(x _(C,t))≈MV_(R)(x _(R,t))=MV_(R)(x _(C,t)+DV_(t)(x _(C,t)))

It should be noted that we still need an estimate for the disparity in the current access unit (current time instant) in order to prediction the motion inside the current view based on the motion inside the reference view. However, the accuracy of the disparity estimate is less critical, since it is only used for accessing motion data in the reference view. The motion compensation operations as well as the coding of motion data is done based on blocks of multiple samples and, furthermore, the motion of neighboring samples or blocks is often very similar. Nonetheless, an accurate estimate of the disparity generally improves the prediction of motion parameters. The estimated disparity vector DV_(t)(x_(C,t)) can also be used as a disparity vector for disparity-compensated prediction (i.e., using the picture of the current access unit in a reference view as reference picture), which can represent a special mode of the motion and disparity-based prediction of motion parameters.

Derivation of Candidate Motion or Disparity Data

In the following, we describe the basic derivation of motion data for a given block of the current picture in a particular view (that is not the backwards compatible base view) such as view 22 in FIG. 1, given motion data of an already coded reference view or of a set of already coded reference views such as 20 in FIG. 1. For this description, we assume that an estimate of the depth data for the current picture is given such as 64 in FIG. 1. Later, we describe how this depth estimate can be derived and how the derived motion data can be used for an efficient coding of the current view. The depth data 64 for the current picture are either given by a pixel-wise or a block-wise depth map. If a pixel-wise depth map is given, the depth map specifies a depth value for each sample (or each luminance sample) of the associated picture. If a block-wise depth map is given, the depth map specifies a depth value for an M×N block of samples (or luminance samples) for the associated picture. For example, a depth value for each block of the smallest possible block size (e.g., 4×4 or 8×8 block) that can be used for motion compensation could be specified. Conceptually, a depth value d given by a sample of the depth map, specifies a function of the real-world depth z, which is the distance between the associated real-world object point (the projection of the real-world object point is the image sample at the given position) and the camera: d=f _(dz)(z)

The depth values are given with a particular precision (furthermore, depth values are often estimated, since the actual depths are usually not known). In most cases, depth values are given by integer numbers. Given the depth values and particular camera parameters (such as the focal length, distance between cameras, minimum and maximum depth values, or functions of these parameters), the depth value d can be converted into a disparity vector v=[v_(x),v_(y)]^(T): v(x)=f _(vd)(d(x),x), where f_(vd) specifies the function that maps a depth value d at sample location x=[x,y]^(T) to a disparity vector. In a particular important setup is the one-dimensional parallel camera configuration, which is characterized by the following properties:

-   -   all cameras of the camera array are of the same type and have         the same focal length     -   the optical axes of all cameras are parallel and lie inside the         same plane     -   the scan lines of the image sensors are parallel to the plane         that contains the optical axes

In this case, the vertical component of the disparity vector is zero, v=[v,0]^(T). Each real-world object point has the same vertical location in all views. Its horizontal location depends on the depth of the object point. The difference between the horizontal locations is given by the disparity v=f _(vd)(d).

In an important case, the relationship between the real-world depth z and the depth values d is given in a way that a linear relationship between the disparity v and the depth value d is obtained v=m _(vd) ·d+n _(vd), where m_(vd) and n_(vd) are given by the camera parameters. The depth values d are usually given as integer values. And for internal calculations it is usually also advantageous if the obtained disparity values are integer values. For example, the disparity v can be expressed in the same units that is used for the motion/disparity vectors in motion/disparity-compensated prediction (e.g., half-, quarter, or eighth-sample accuracy). In this case, the integer values for the disparity can be obtained by the integer equation v=[(m]* _(vd) ·d+n* _(vd))»u _(vd), where “»” specifies a bit shift to the right (in two's complement arithmetic), and m*_(vd) and n*_(vd) are scaled (and rounded) versions of m_(vd) and n_(vd), respectively. Using the described basic relationships between the given depth values and the actually disparity, we describe advantageous embodiments for using motion information that are derived based on already coded motion information in one or more reference views and the given estimated depth values. Method 1: Switched Motion/Disparity Vector Prediction

In an advantageous embodiment of the invention, the underlying multiview video coding scheme such as for modules 24, 26, 80 and 82 includes a mode, in which the following parameters are transmitted as part of the bitstream 21:

-   -   reference picture index specifying a particular (temporal or         inter-view) reference picture of a given a list of reference         pictures. If the given list of reference pictures consists of a         single element, this index is not transmitted but inferred at         the decoder side. The reference picture include temporal and/or         inter-view reference pictures.     -   a motion/disparity vector predictor index specifying a         motion/disparity vector predictor of a given list of         motion/disparity vector predictor candidates. If the list of         motion/disparity vector predictor candidates consist of a single         element, this index is not transmitted but inferred at the         decoder side. For at least one block of a picture, the list of         motion/disparity vector predictor candidates includes a         motion/disparity vector that is derived based on given         depth/disparity information and motion information in an already         coded view.

In addition, a motion/disparity vector difference specifying the difference between the motion/disparity vector used for motion/disparity-compensated prediction and the chosen predictor (indicated by the transmitted index into the motion/disparity vector predictor candidate list) can be transmitted as part of the bitstream. In one embodiment, this motion/disparity vector difference can be coded independently of the reference index and the chosen predictor. In another embodiment of the invention, the motion/disparity vector difference is coded depending on the transmitted reference index and/or the chosen predictor. For example, a motion/disparity vector difference could only be coded if a particular motion/disparity predictor is chosen.

The reference picture list and the motion/disparity vector predictor candidate list are derived in the same way at encoder and decoder side. In specific configurations, one or more parameters are transmitted in the bitstream, for specifying how the reference picture lists and/or motion/disparity vector predictor candidate lists are derived. For the advantageous embodiment of the invention, for at least one of the blocks of a picture in a dependent view such as 22, the list of motion/disparity vector predictor candidates contains a motion or disparity vector predictor candidate that is derived based on the given (estimated) depth values or based on the given (estimated) depth value and the motion parameters of an already coded view. Beside the motion/disparity vector predictor that is derived based on the given depth values and motion parameters of already coded views, the candidate list of motion/disparity vectors predictors may contain spatially predicted motion vectors (for example, the motion/disparity vector of a directly neighboring block (left or above block), a motion/disparity vector that is derived based on the motion/disparity vectors of directly neighboring blocks) and/or temporally predicted motion/disparity vectors (for example, a motion/disparity vector that is derived based on the motion/disparity vector of a co-located block in an already coded picture of the same view). The derivation of the motion/disparity vector candidate that is obtained by using the given depth data 64 and the already coded motion parameters such as 42 of other views such as 20 can be performed as described in the following.

Derivation Based on the Derivation of a Representing Depth for the Current Block

In a first advantageous embodiment of the invention, first a representing depth value d for the given block 50 is obtained based on the given sample-based or block-based depth map. In one advantageous embodiment, a particular sample location x of the given block 50, which may be the top-left sample, the bottom-right sample, a middle sample, or any other particular sample, is considered. The depth value d=d(x) that is associated with the sample (as given by the given block-wise or sample-wise depth maps 64) is used as representing depth value. In another advantageous embodiment, two or more sample locations x_(i) of the given block (for example, the corner samples or all samples) are considered and based on the associated depth values d_(i)=d(x_(i)), a representing depth values d is calculated as a function of the depth values d_(i). The representing depth value can be obtained by any function of the set of depth values d_(i). Possible functions are the average of the depth values d_(i), the median of the depth values d_(i) the minimum of the depth values d_(i), the maximum of the depth values d_(i), or any other function. After obtaining the representing depth value d for the given block, the motion/disparity vector prediction proceeds as follows:

-   -   If the reference index that is coded for the block 50 refers to         an inter-view reference picture (i.e., a coded picture at the         same time instance as the current picture, but in an already         coded view such as 20), the representing depth value is         converted to a disparity vector V based on given camera or         conversion parameters as described above, v=f_(vd)(d), and the         motion/disparity vector predictor is set equal to this disparity         vector v.     -   Otherwise (the reference index refers to a temporal reference         picture (i.e., an already coded picture of the same view (such         as 22)), the motion vector predictor is derived based on a given         reference view or a set of reference views such as 20. The         reference view or the set of reference views are either         determined by a particular algorithm or a signaled in the         bitstream 14. As an example, the reference view can be the         previously coded view for the same time instant, or it can be         the already coded view (for the same time instant) that has the         smallest distance to the current view, or any other of the         already coded view determined by a particular algorithm. The set         of already coded view can be the set of already coded views for         the current time instant or any subset of this set.

If a single reference view is used, the motion vector predictor is derived as follows. Based on the camera parameters for the current view 22 and the reference view 20 or the corresponding conversion parameters, the representing depth d is converted into a disparity vector v=f_(vd)(d). Then, given the disparity vector v, a sample location x_(r) in the reference view 20 is determined. Therefore, a particular sample location x_(r) of the current block 50 is considered, which may be the top-left sample of the block, the bottom-right sample, a middle sample, or any other sample of the block. The reference sample location x_(r) is obtained by adding the disparity vector v to the particular sample location x inside the current block. If the disparity vector v is given with sub-sample accuracy, it is rounded to sample accuracy before it is added to the sample location. Given the reference sample location x_(r), the block 40 (a block is a set of sample that is associated with unique prediction parameters) in the picture 32 t ₁ (at the current time instant as the current picture) of the reference view 20 that covers the reference sample location x_(r) is determined. If this reference block 40 is coded in an inter-coding mode (i.e., a mode that employs motion-compensated prediction, including the SKIP or MERGE mode), the reference picture or reference pictures that are used for predicting this block are investigated. Let t_(C,R) be the time instant of the reference picture (in the current view) that is referred to be the reference index that is coded for the current block 50. And let t_(R,R) ^(i) be the time instants of the reference picture that are used for predicting the reference block (which covers the sample location x_(r)) in the reference view 20. If one or more of the reference pictures that are used for predicting the reference block 40 are pictures at the same time instant as the reference picture given by the reference index for the current block 50 (i.e., if t_(C,R) is equal to any of the values t_(R,R) ^(i)), the corresponding motion vectors 42 are used for deriving the motion vector predictor for the current block 50. If exactly one of the time instants t_(R,R) ^(i) is equal to t_(C,R), the motion vector predictor for the current block 50 is set equal to the motion vector 42 for the reference block 40 that is associated with the corresponding value of t_(R,R) ^(i). If two or more of the time instants t_(R,R) ^(i) are equal to t_(C,R), the motion vector predictor is set equal to a given function of the associated motion vectors for the reference block 40. A possible function is to use the first motion vector (in any particular order, e.g. by using the first hypotheses with t_(R,R) ^(i)=t_(C,R)), another possible function is to use the average of the motion vectors, a further possible function is to use the median of the candidate motion vectors, or to use the median of the motion vector components for deriving all components of the motion vector predictor. If none of the associated reference pictures has a time instant t_(R,R) ^(i) equal to t_(C,R), the motion vector predictor is marked as not available. In an advantageous embodiment of the invention, a non-available motion vector predictor is not included in the list of motion/disparity vector predictor candidates. In another advantageous embodiment of the invention, a non-available motion vector predictor is included in the list of motion/disparity vector predictor candidates for increasing the robustness of the parsing algorithm, but it cannot be chosen by an encoder. In another advantageous embodiment of the invention, a non-available motion vector predictor is replaced by another defined motion vector, which may be, for example, the zero vector, or a motion vector that is derived using the motion vectors of a neighboring block. Instead of the time instants (t_(R,R) ^(i),t_(C,R)), other parameter that specify a similar measure can be used for determining whether a motion parameter set (consisting of a reference picture index and a motion vector) can be used for deriving the motion vector predictor. For example the picture order count (similarly defined as in H.264) could be used or the reference index could be used.

If a set of two or more reference views are used, the motion vector predictor can also be derived based on information in all reference views. In an advantageous embodiment, the reference views are ordered in a particular order. As an example, the reference views can be ordered in the order in which they are coded. Or as another example, the reference views are ordered in the order of increasing distances to the current view. Then, the first reference view of the ordered set is investigates and the corresponding motion vector predictor is derived. If this motion vector predictor is marked as available (i.e., it is not marked as not available), the motion vector predictor is used. Otherwise, if the motion vector predictor is marked as not available, the next reference view in the given ordered set is investigated, etc. In another advantageous embodiment of the invention, all reference views of the given set are investigated and the candidate set of motion vectors consists of all corresponding motion vectors that are associated with a reference picture for which the associated time instant t_(R,R) ^(i) is equal t_(C,R). The final motion vector predictor is then derived by a function of the set of candidate motion vectors. A possible function is to use the first motion vector (in any particular order), another possible function is to use the average of the motion vectors, a further possible function is to use the median of the candidate motion vectors, or to use the median of the motion vector components for deriving all components of the motion vector predictor.

For further illustration, the basic process for deriving a motion vector for the current block 50 _(C) given the motion in a reference view 20 and a depth map estimate for the current picture 32 t ₂(T) (using a particular sample position inside the current block 50 _(C)) is depicted in FIG. 4 using similar reference signs as in FIG. 1 in order to ease the mapping of the description of FIG. 4 onto FIG. 1 so as to serve as a possible source of more detailed explanation of possible implementations. Given a sample location x in the current block 50 _(C) and a depth value d for this sample location (which is given by the estimate 64 of the depth map), a disparity vector 102 is derived, and based on this disparity vector 102, a reference sample location x_(R) in the reference view 20 is derived. Then, the motion parameters 42 _(R) of the block 40 _(R) in the reference view picture 32 t ₁(T) that covers the reference sample location x_(R) are used as a candidate for the motion parameters for the current block 50 _(C) in the current view 22. Or alternatively, a subset of the motion parameters of the reference block is used for the current block 50 _(C). If the reference index for the current block 50T is given, only motion parameters 42 _(R) of the reference block 40 _(R) that refer to the same time instant T (or picture order count or reference index) as the given reference index for the current block 50 _(C) or considered.

Derivation Based on Multiple Depth Values for the Given Block

In a second advantageous embodiment of the invention, the current block 50 _(C) is not represented by a representing depth, but different depth values for different sample locations inside the block are derived and used for deriving a set of candidate motion vector predictors. Given the current block a set of sample locations x^(i) are considered. The set of sample locations can include the top-left sample, the top-right sample, the bottom-right sample, the bottom-left sample, or a middle sample of the block. For each of the sample locations x^(i), a depth value d^(i) is assigned by the given depth map. Depending on whether the given reference index refers to an temporal or inter-view reference, the following applies.

-   -   If the reference index that is coded for the block 50 _(C)         refers to an inter-view reference picture (i.e., a coded picture         at the same time instance as the current picture, but in an         already coded view), the depth values d^(i) are converted to a         disparity vectors v^(i) based on given camera or conversion         parameters as described above, v^(i)=f_(vd)(d^(i)). Then, the         motion/disparity vector predictor is derived as a function of         these disparity vectors v^(i). The motion/disparity vector         predictor can be set equal to the disparity vectors v^(i) that         occurs most often, or it can be set to the median (or         component-wise median) of the disparity vectors v^(i), or it can         be set to the average of the disparity vectors v^(i), or it can         be determined by any other function of the disparity vectors         v^(i).     -   Otherwise (the reference index refers to a temporal reference         picture (i.e., an already coded picture of the same view)), the         motion vector predictor is derived based on a given reference         view or a set of reference views. For each sample location         x^(i), a depth value d^(i) is derived and mapped to a disparity         vector v^(i). Then, for each disparity vector v^(i) (marked as         available), a motion vector m^(i) is derived by any of the         algorithms specified above (for the first advantageous         embodiment). Then, the final motion vector predictor is given by         a function of the motion vectors m^(i). The motion vector         predictor can be set equal to the motion vector m^(i) that         occurs most often, or it can be set to the median (or         component-wise median) of the motion vectors m^(i), or it can be         set to the average of the motion vectors m^(i), or it can be         determined by any other function of the motion vectors m^(i).         Method 2: Mode for which all Associated Motion Parameters are         Derived

In another advantageous embodiment of the invention, the multiview video coding scheme includes a coding mode, in which all motion parameters (including the number of hypotheses, the reference indices, and the motion vectors) are derived based on a given depth map 64 and the motion parameters 42 of an already coded view 20. In a particular embodiment of the invention, this mode can be coded as a candidate of a list of candidate motion parameters (as it is used in the merge syntax in the current HEVC working draft). That means, encoder and decoder derive a list of motion parameter candidates for a block in the same way, where one of the motion parameter candidates are the motion parameters that are derived based on the motion of an already coded view 20. Then, an index is coded that signals to the decoder which of these motion parameter candidates is used. In context of the merge syntax, it can be argued that the current block is merged with a “co-located” (in spirit of representing a similar content) block in a reference view. In another embodiment, a specific syntax element signals the usage of the new coding mode. In a slightly modified version, the number of motion hypotheses that are used for generating the prediction signal can be explicitly signaled inside the bitstream, and only the reference indices and the associated motion vectors are derived. In another modified version, motion vector differences can be additionally transmitted in order to refine the derived motion parameters.

Derivation Based on Multiple Potential Reference Indices

In a first advantageous embodiment of the invention, the derivation of the motion parameters for the current block 50 _(C) uses any of the concepts described for method 1 above and considers more than one potential reference index. In the following, we first describe how a reference index for a particular motion hypothesis (and reference list) and the associated motion vector can be derived. As a first step, an ordered set of reference indices for a given reference list is determined. This can be for example just a single reference index (e.g., the first index for the reference list or the first index representing a temporal reference picture), or it can consist of the first two indexes of the reference list, or it can consists of all reference indices of the reference list, or it can consist of the first reference index that represents a temporal reference picture and the first reference index that is not equal to the first reference index that represents a temporal reference picture (i.e., the second temporal reference picture in the list or the first inter-view reference picture). Any other defined set of reference indices is possible. Given the ordered set of reference indices, the first reference index is considered and a motion vector for this reference index is derived by any of the embodiments described for method 1 above. If the derived motion vector is marked as not available, the next reference index is considered and the corresponding motion vector is derived. This process is continued until an available motion vector is returned or all reference indices of the list have been tested. If no available motion vector is found, the final motion parameters are marked as not available. In one configuration, not available motion parameters are not inserted into the candidate list of motion parameters. In a second configuration, not available motion parameters are inserted into the candidate list of motion parameters (for parsing robustness), but an encoder is not allowed to choose not available motion parameters. In a third configuration, a not available motion parameters are replaced by particular motion parameters, which may be, for example, a zero reference index and a zero motion vector or a reference index and motion vector that are derived based on the motion parameters in a spatial neighborhood of the current block. If the new coding mode is signaled by a particular syntax element and the derived motion parameters are not available, the corresponding syntax element is either not transmitted (and the coding mode is not used) or the encoder is not allowed to select the value for the syntax element that specifies the usage of the new coding mode or the not available motion parameters are replaced by a particular motion parameters (see above).

If the number of motion hypotheses or the number of used reference lists is explicitly coded, a set of motion parameters consisting of a reference index and a motion vector is determined for each motion hypothesis or reference list as specified above. If the number of motion hypotheses or the number of used reference lists is not explicitly coded, the number of motion hypotheses or the employed reference lists are also derived based on the actual coded motion parameter in the reference view(s). Given a maximum number of motion hypotheses or the maximum set of reference lists that can be used, for each of the motion hypothesis (reference lists) a set of motion parameters is derived as described above. Then, the number of motion hypotheses (set of used reference picture lists) is given by the hypotheses (reference lists) for which the derived motion parameters are marked as available. As an example, if we have two potential motion hypotheses and for both motion hypotheses a valid set of motion parameters (reference index and motion vector) is derived, the new coding mode specifies bi-prediction with the derived motion parameters. If, however, only for one of the hypotheses (reference lists) a valid set of motion parameters is derived, the new coding mode specifies uni-directional prediction (one hypothesis) with the set of valid motion parameters. If for none of the motion hypotheses (reference lists) a valid set of motion parameters is derived, the complete set of motion parameters is marked as not available. In this case, the set of motion parameters is either not added to the list of candidate motion parameters, or it is added (for parsing robustness) but not used by an encoder, or it is replaced by a particular defined set of motion parameters (e.g., with one motion hypothesis, a reference index equal to 0 and a motion vector equal to 0). It would also be possible to check another set of reference indices for one or more of the potential motion hypotheses.

Derivation Based on a Single Representing Depth Value

In a second advantageous embodiment of the invention, first a reference block in the reference view is derived and then the motion parameters of this block are used as motion parameter candidates for the current block. Here, the number of motion hypotheses as well as the reference indices and motion vectors are copied from the reference block in the reference view. The basic concept for this embodiment is illustrated in FIG. 2 and has been briefly described above. First, a representing depth value d, and based on this depth value a disparity vector v, and a reference sample location x_(R) are derived by any of the algorithms described for method 1. Then, the block (also referred as reference block) in the reference view that covers the reference sample location x_(R) is considered. The motion parameters for the current block (or one candidate for the motion parameters) are set equal to the motion parameters of the derived reference block. It is also possible that the motion parameters (in particular the reference indices and the number of motion hypotheses) are modified, for example in the following scenarios:

-   -   If the reference picture list for the reference view is         constructed in a different way than the reference picture list         for the current view (i.e., a particular reference index does         not always refer to the same access unit for both lists), a         reference index for the current block can be modified in a way         that it refers to a picture at the same time instant (or a         picture with the same picture order count) as the corresponding         reference picture in the reference view.     -   If a reference index in the reference view refers to an         inter-view reference picture, the reference index for the         current view can be modified in a way that it also refers to a         selected inter-view reference picture (for example, the same         inter-view reference picture as the current view or the         reference picture that is represented by the reference view). In         this case, also the motion vector has to be replaced with a         disparity vector, which can be obtained by converting the         representing depth d to a disparity vector.     -   If not for all reference pictures that used in the reference         block a corresponding picture (same time instant or picture         order count or reference index) is available in the reference         list for the current block, the motion hypotheses that refer to         reference pictures that are not available for the current blocks         can be considered as not existing.     -   If the reference block is intra coded, the motion parameters can         be replaced with motion parameters for disparity compensated         prediction. For example, the reference index can be set in a way         that it refers to the reference view picture and the motion         vector can be set equal to the disparity vector that is obtained         by converting the representing depth to a disparity vector. As         an alternative, the motion parameters could be marked as not         available.         Combination with Method 1

In an embodiment, the coding mode described by an embodiment for method 1 (coding of reference index, derivation of a motion vector or motion vector predictor) can be supported in addition to a coding mode described by an embodiment of method 2 (derivation of all motion parameters including the number of motion hypotheses, reference indices, and motion vectors or motion vector predictors).

Method 3: Mode for which all Associated Motion Parameters as Well as the Block Partitioning are Derived

In another advantageous embodiment of the invention, the multiview video coding scheme includes a coding mode, in which different motion parameters for subblocks of the given block are derived based on the motion parameters in an already coded reference view such as 20 and an estimated depth map 64. Or in other words, the multiview video coding scheme includes a coding mode for a block, in which the partitioning of the block 50 _(C) into smaller subblocks as well as the motion parameters associated with the subblocks are derived based on the motion parameters in an already reference view and an estimated depth map.

For this coding mode, a minimum block size is defined, which may be equal to the minimum block size that is supported for motion/disparity-compensated prediction or may be a multiple of the minimum block size that is supported for motion/disparity-compensated prediction. If the given current block 50 _(C) is smaller or equal to the defined minimum block size, the current block 50 _(C) is not split into smaller block for the purpose of motion/disparity compensation and the associated motion parameters are derived as described for any of the embodiments for method 2 above. If the given current block is larger than the defined minimum block size, it is split into subblocks that have a size equal to the defined minimum block size. For each of these subblocks, a set of motion parameters is derived using any of the embodiments for method 2 described above.

If the motion parameters for any of the subblocks are marked as not available (for example, because the corresponding reference block 40 _(R) is coded in an intra-mode or it only uses inter-view prediction), they can be replaced by motion parameters of any of the neighboring subblocks for which the motion parameters are available. Such an algorithm can operate in a way that neighboring blocks are tested in specific defined order (which may depend on the location of the subblocks to be replaced), and the motion parameters of the subblock to be replaced are set equal to the motion parameters of the first subblock in the specified order that has valid motion parameters.

In a particular embodiment of the invention, the obtained subblocks with a given minimum block size specify the partitioning of the given current blocks 50 _(C). In another embodiment of the invention, the obtained subblocks can be combined based on the associated motion parameters in order to form larger blocks that are used for motion/disparity-compensated prediction. The combination of subblocks can proceed in a hierarchical fashion. Therefore, in the first hierarchy stage, sets of four neighboring blocks can be considered. If the number of motion hypotheses and the associated reference pictures and motion vectors are the same for all four subblocks, the four subblocks are summarized to a larger block (with motion parameters that are identical to the motion parameters of the original subblocks). In the next hierarchy stage, four blocks of the next hierarchy level (consisting of 4 original subblocks) are considered. If all four blocks have been summarized to larger blocks in the previous hierarchy stage and the number of motion hypotheses and the associated reference pictures and motion vectors are the same for all four blocks, these four blocks are again summarized to a larger block (with motion parameters that are identical to the motion parameters of the original subblocks). This algorithm in continued up to the highest possible hierarchy level for the given current block. In the extreme case (if the motion parameters of all subblocks are the same), the entire current block is not split but associated with a unique set of motion parameters. In a slightly modified version, 4 blocks are also summarized to a larger block if the motion vectors are not be exactly the same, but the difference (which may be defined as maximum component difference or the absolute value of the vector difference) between the motion vectors is less or equal to a defined threshold (the number of motion hypotheses and the employed reference pictures is still the same). In this case, the motion vectors that are associated with the larger block are determined as a function of the motion parameters of the 4 subblocks. Possible functions are the average of the motion vectors, the median (or component-wise median) of the motion vectors, the motion vector of any particular subblock, or the motion vector that occurs most often in the four subblocks).

In an embodiment of the invention, the coding mode described by an embodiment for method 1 (coding of reference index, derivation of a motion vector or motion vector predictor) can be supported in addition to a coding mode described by an embodiment of method 3 (derivation of the blocks splitting as well as all motion parameters including the number of motion hypotheses, reference indices, and motion vectors or motion vector predictors). In addition, a coding mode according to any embodiment of method 2 may be supported.

Coding of Motion and Disparity Data

As already described above, the usage of coding modes representing embodiments of the invention, needs to be signaled to the decoder. This can be realized in different ways. In one version, a particular syntax element (which may be a flag) can be inserted into the syntax, which signals whether a conventionally derived motion vector predictor (or motion vector or motion parameter set) is used or whether a motion vector predictor (or motion vector or motion parameter set) that has been derived using a depth map estimate and motion parameters of an already coded view is used. In another version, the motion vector predictor (or motion vector or motion parameter set) that has been derived using a depth map estimate and motion parameters of an already coded view can be inserted into a candidate list of conventionally derived motion vector predictors (or motion vectors or motion parameter sets) and an index is transmitted which signals which motion vector predictor (or motion vector or motion parameter set) is used. The particular syntax element or the index into a candidate list can be transmitted using fixed-length coding, variable-length coding, arithmetic coding (including context-adaptive binary arithmetic coding), or PIPE coding. If context-adaptive coding is used, the context can be derived based on the parameters (for example, the particular syntax element or the index into a candidate list) of neighboring blocks.

In an advantageous embodiment of the invention, the multiview video coding scheme includes a coding mode for which one or more motion hypotheses are signaled by transmitting a reference picture index, a motion vector predictor index, and a motion vector difference for each motion hypothesis. For this coding mode, a list of candidate motion vector predictors is derived based on the transmitted reference picture index and the transmitted index signals which one of the motion vector candidates is used. By using the embodiment, one of the motion vector candidates (for at least one block) is derived based on a depth map estimate and motion parameters of an already coded view (see method 1 above). In a slightly modified version, a motion vector difference is not transmitted but inferred to be equal to 0 (either for all motion vector candidates or only for the motion vector candidate that has been derived based on a depth map estimate and motion parameters of an already coded view.

In another advantageous embodiment of the invention, the multiview video coding scheme includes a coding mode for which one or more motion hypotheses are signaled by transmitting motion parameter index (or merge index). For this coding mode, a list of candidate sets of motion parameters (including the number of motion hypotheses, the reference indices, and motion vectors) is derived. By using the embodiment, one of the candidate sets of motion parameters (for at least one block) is derived based on a depth map estimate and motion parameters of an already coded view (see methods 2 and 3 above). In a particular version of this embodiment, the candidate set of motion parameters (for at least one block) that is derived based on a depth map estimate and motion parameters of an already coded view includes partitioning information for the current block (see method 3 above). In a slightly modified version of this embodiment, motion vector differences can additionally be transmitted (potentially depending on the selected set of motion parameters).

In another embodiment of the invention, the multiview video coding scheme includes a coding mode corresponding to method 2 or 3 and the syntax includes a flag which specified whether this coding mode is used.

Derivation of Depth Map Estimates for the Current Picture

The derivation of motion parameters for a block of the current picture 50 _(C) based on the motion parameters of already coded views such as 20, as described so far, involves that an estimate 64 of the depth map for the current picture is available. As mentioned above, this depth map estimate 64 can specify a sample-wise depth map (a depth value is specified for each sample of the current picture) or a block-wise depth map (a depth value is specified for blocks of samples). The depth map estimate 64 may be derived based on already coded parameters, such as depth maps or disparity vectors and motion parameters. In principle, the possibilities for deriving a depth map estimate 64 for the current picture can be categorized into two classes. For one class, the depth map estimate is derived based on actually coded depth maps. The corresponding possibilities described below involve that the coded depth maps are present in the bitstream (before they are used). Concepts of the second class do not require that depth maps are coded as part of the bitstream. Instead, the depth map estimate is derived based on coded disparity vectors. The second class of procedures can be applied independently of whether depth maps are coded as part of a bitstream. This was the case discussed above with respect to FIGS. 1 and 2 for which the following description in so far provides individually transferrable details regarding individual aspects. It should also be noted that, when depth maps are coded, both classes of methods can be applied. It is also possible to select different methods for different frames.

In the following, the basic concept and advantageous embodiments for deriving depth maps estimates (with and without coded depth maps) are described.

Class 1: Derivation Based on Coded Depth Maps

If the depth map that is associated with the current picture 32 t ₂(T) would be coded before the current picture, the reconstructed depth map could directly be used as an estimate of the real depth map for the current picture. It is also possible to pre-process the coded depth map (e.g., by applying a filtering it) and use the result of the pre-filtering as the estimate of the depth map that is used for deriving motion parameters.

In most configurations, the depth map that is associated with a particular picture is coded after the picture 32 t ₂(T) (often directly after the associated picture). Such a configuration allows that coding parameters (such as motion parameters) that are transmitted for coding the conventional video pictures can be used for predicting the coding parameters that are used for coding the depth maps, which improves the overall coding efficiency. But in such a configuration, the depth map that is associated with a picture cannot be used as an estimate for the depth map in deriving the motion parameters 54. However, the depth map for an already coded view (of the same access unit) such as 20 is usually available and can be used for deriving an estimate of the depth map of the current picture. At least, the depth map of the base view (independent view) 20 is available before coding any dependent view 22. Since the depth map of any view represents the geometry of the projected video scene to some extent (in combination with camera parameters such as focal length and the distance between cameras) it can be mapped to another view. Consequently, if the depth map for the current picture 32 t ₂(T) is not available, the coded depth map for an already coded view of the same access unit 20 is mapped to the current view and the result of this mapping is used as depth map estimate.

In the following we describe a particular algorithm for realizing this mapping. As described above, each depth value d corresponds to a displacement vector v between two given views. Given transmitted camera or conversion parameters, a depth value d can be converted to a displacement vector my the mapping v=f_(vd)(d). Hence, given a depth value d at a particular sample location x_(R) in the reference depth map (already coded), the sample location x_(C) of the same depth value in the current depth map is obtained by adding the disparity vector to x_(R), x_(C)=x_(R)+v. Hence, each depth value of the reference depth map can be mapped to a sample location of the current depth map in order to obtain a depth map estimate 64 for the current picture. However, since parts of objects that are visible in one view are not visible in another view, there are sample location in the depth map for the current view 22 to which more than one depth values is assigned and there are sample location in the depth map for the current view to which no depth values is assigned. These sampled location may be processed as follows:

-   -   If more than one depth value is assigned to a particular sample         location, it means that a foreground object is displaced in         front of a background object. Consequently, the depth value d         (of the potential depth values) that represents the smallest         distance to the camera is assigned to such a sample location.     -   If more no depth value is assigned to a particular sample         location, it means that a foreground object has moved and the         previously covered background is visible. The best that can be         done for such regions is to assume that the disoccluded         background has the same depth than the neighboring background         samples. Hence, regions to which no depth value has been         assigned are filled with the depth value of the surrounding         samples that represents the largest distance to the camera.

This algorithm is specified in more detail in the following. For simplifying the following description, we assumed that larger depth values represent smaller distances to the camera than smaller depth values (but the algorithm can easily be modified for the opposite assumption):

-   -   1. All samples of the depth map (estimate) for the current         picture are set to an undefined depth value (e.g., −1).     -   2. For each sample location X_(R) of the reference depth map,         the following applies:         -   a. The depth value d at the sample location x_(R) is             converted to a disparity vector v using the given camera or             conversion parameters, the disparity vector v is rounded to             sample accuracy (if applicable), and the sample location             inside the current picture is derived by             x_(C)=x_(R)+v=x_(R)+[round(f]_(vd)(d)).         -   b. If the depth value at sample location x_(C) in the             current picture has an undefined value, the depth value at             sample location is set equal to the depth value d.         -   c. Otherwise, if the depth value at sample location x_(C) in             the current picture has a defined value d_(x) with d_(x)<d,             the depth value at sample location is modified and set equal             to the depth value d.     -   3. The regions in the current depth map that have undefined         depth values are filled by a particular hole filling algorithm.         For such a hole filling algorithm, the depth value of the         background that is uncovered in the current view is derived         based on the samples of the surrounding depth values. As an         example, the smallest depth map value of the surrounding samples         can be assigned. But more sophisticated hole filling algorithms         are possible.

The algorithm for mapping a depth map of a given view to a different view is further illustrated in FIG. 5 on the basis of a very simple example. FIG. 5 illustrates a possible process for mapping a depth map such as 32 t ₁(T) given for one view 20 to another view 22. At the left hand side, the given depth map for the reference view is shown, where the shaded area represents a background and the white area represents a foreground object; in the middle of FIG. 5, middle, the converted depth map obtained by displacing the samples of the given map with the disparity vectors that correspond to the depth values and keeping the foreground object for locations to which more than one sample is projected, is shown. The black area represents on disoccluded area to which no sample has been projected. FIG. 5, right, shows the converted depth map after filling the disoccluded areas by the depth value for the background, i.e. ba background filling.

In a particular embodiment of the invention, the hole filling can realized by a particularly simple algorithm which processes the lines of the converted depth map separately. For each line segment that consists of successive undefined depth values, the two surrounding values are considered, and all depth samples of the line segment are replaced with the smaller of these two depth values (background depth). If the line segment has only one surrounding depth value (because it is located at the image border), the depth samples of the line segment are replaced with this value. If complete lines have undefined values after this process, the same process is applied for the columns of the depth map.

Although the algorithm above has been described for sample-wise depth maps, it can also be applied to block-wise depth maps (resulting in a lower complexity) or the given sample-wise depth map for the reference view can first be converted into a block-wise depth maps (by downsampling) and then the algorithm can be applied for the block-wise depth map.

Class 2: Derivation Based on Coded Disparity and Motion Vectors

If no depth maps are coded as part of the bitstream, an estimate for the depth map can be generated by using the coded motion and disparity vectors. A basic idea of the following concept can be summarized as follows. The decoding of a (multiview) video sequence generally starts with a random access unit. The picture for the base view in a random access unit is intra coded without referencing any other picture. The pictures for dependent views in the random access unit can be intra coded or predicted using disparity-compensated prediction. Typically, most blocks will be coded by disparity-compensated prediction, since it usually gives better prediction results than intra prediction. Since, the coded disparity vectors (which are used for disparity-compensated prediction) can be converted into depth values (using the inverse function) f_(vd) ⁻¹, the disparity vectors can be directly used for generating a block-based depth map that is associated with a dependent view in a random access unit (the depth for intra-coded blocks can be estimated based on the depth for surrounding disparity-compensated block). Then, this obtained depth map can be mapped to the base view. The next picture for the base view is typically coded using mostly motion-compensated prediction. Here, it can be assumed that the motion of the depth data is the same as the motion for the texture information (a depth and an associated texture sample belong to the same object point). Given this assumption, the estimated depth data for the first picture in the base view can be motion-compensated for obtaining an estimate for the depth map of the base view in the current access unit. And then, this (motion-compensated) depth map estimate for the base view can be mapped to a dependent view for obtaining a depth map estimate for the current picture (in the current view). If more than two views are coded, the creation of depth map estimates for the third view, fourth view, ect. can be simplified, since we also have a depth map estimate for the first two views of the access unit. One of these depth map estimates (advantageously the base view) can be mapped to the third, fourth, or any following view in order to generate a depth map estimate for this view.

The idea of generating a depth map estimate is further illustrated by some figures (showing the processing steps for multiview coding with two views as they are performed by depth estimator 28). The coding/decoding starts with a random access unit, for which the base view picture 32 t ₁(0) is intra-coded and the non-base-view pictures 32 t ₂(0) are coded using only intra and inter-view prediction (but no motion-compensated prediction). After coding the second view 22 in the random access unit “0”, a block-based depth map estimate for this second view 22 is generated 120 using the coded disparity vectors 122 for this view 22, as illustrated in FIG. 6. This depth map estimate 64 ₂(0) for the second view 22 is then mapped 124 to the first view (base view) 20 and a depth map estimate 64 ₁(0) for the first view 20 is obtained. It should be noted that for the second view 22 of a random access unit, the derivation of motion/disparity parameters based on the motion parameters of the base view and a disparity estimate cannot be used, because no estimate of the depth map is available when the second view 22 of a random access unit is coded.

If a third view is coded, the depth map estimate of any of the first two views (advantageously the second view) can be mapped to the third view resulting in a depth map estimate for the third view, which can be used for deriving motion parameters for the third view. And after coding the third view, a block-based depth map can be generated using the coded disparity vectors for the third view (which can than later be used for generating a depth map estimate for any following view). For any following view, basically the same process as for the third view can be used.

The pictures of the base view in non-random-access units are typically mainly coded by motion-compensated prediction, since motion-compensated prediction usually gives better coding efficiency than intra coding. After a picture of the base view is coded, an estimate of the depth map for this picture is generated 140 (cp. 71 in FIG. 1) using the motion parameters 42(1) for the picture 32 t ₁(1), as illustrated in FIG. 7. Therefore, each block of the new depth map estimate 641(1) is created 140 by motion-compensating the depth map estimate 64 ₁(0) (cp. 74 in FIG. 1) for the corresponding reference picture or pictures. The reference pictures and corresponding motion vectors 42(1) that are used are the reference pictures and motion vectors that are coded in the data stream for the associated picture. The depth samples for intra-coded blocks can be obtained by spatial prediction. This depth map estimate for the base view is than mapped 142 (cp. 76 in FIG. 1) into the coordinate system for the second view in order to obtain a depth map estimate 642(1) for the second view which can be used for deriving motion parameters, i.e. to perform inter-view redundancy reduction.

For any further coded view, a depth map estimate can be generated by mapping the depth map estimate for any already coded view (base view, second view, etc.) to the corresponding view.

After actually coding the picture of the second view (or any following view), the associated depth map estimate can be updated 160 (cp. 77 in FIG. 1) using the actually coded motion and disparity vectors, as illustrated inFIG. 8. For blocks that are coded using disparity compensation, the depth map samples can be obtained by converting 162 the coded disparity vectors 60 to depth values as described above. For blocks that are coded using a motion-compensated mode, the depth samples can be obtained by motion compensating the depth map estimate for the reference frame 32 t ₂(0). Or alternatively, a depth correction value, which is added to the current depth map estimate 64 ₂(1), can be derived based on the coded motion parameters 42(1) and 54(1) for the current and for the reference view. The depth samples of intra coded blocks can be predicted using spatial prediction or using the motion parameters of neighboring blocks. After an updated depth map estimate 74 for the second view has been generated, this depth map estimate 74 is mapped 164 (cp. 78 in FIG. 1) to the base view 20 for obtaining a depth map update 64′₁(1) (cp. 74 in FIG. 1) for the base view 20.

If more than two views are coded, the depth map update process for these views is the same as for the second view. However, the base view depth map is only updated after the second view has been coded.

The motion compensation operations for depth maps can be either performed using the coded sub-sample accurate motion vectors. It is, however, often advantageous (from a complexity as well as coding efficiency point of view), if the motion compensation operations for depth maps are performed with sample (or even block) accuracy. Therefore, the actually coded motion vectors are rounded to sample or block accuracy and these rounded vectors are used for performing the motion compensation. Furthermore, the described concept can be applied for sample-wise as well as block-wise depth map estimates. The advantage of using block-based depth maps is a lower complexity and memory requirement for all processing steps. With block-based depth maps, each depth sample represents the depth for a block of samples of the associated picture (e.g., 4×4 blocks or 8×8 blocks). All described operations can be performed for block-based depth maps in a straightforward way (i.e., by simply considering a lower resolution of the depth maps—one depth sample just represents multiple instead of one texture sample).

Besides the mapping of a given depth map from one view to another (which has been described above), the algorithm contains the following basic steps:

-   -   Creating a depth map based on disparity vectors for a picture of         a random access unit.     -   Temporal prediction of the base view depth map using the motion         parameters of the associated picture.     -   Update of a depth map estimate using actually coded motion and         disparity vectors for the associated picture.

Particular embodiments for these algorithmic steps are described in the following.

Creation of a Depth Map for a Picture in a Random Access Unit

In a particular embodiment of the invention, the creation of a depth map for a picture of a dependent view in a random access unit proceeds as follows. In general, such a picture contains blocks that are coded using disparity-compensated prediction as well as blocks that are intra coded. First, all blocks that are coded using disparity-compensated prediction are considered. The disparity vectors are converted into depth values and these depth values are assigned to the corresponding samples of the depth map. If two or more motion hypotheses are used, either one hypothesis is selected or the final depth value is set equal to a function of the depth values for the individual motion hypotheses (for example, the average, the median, the maximum, or the minimum). After assigning the depth values for all disparity-compensated blocks, the depth values for intra coded blocks are obtained by spatial intra prediction. In one version, these samples can be obtained by using the same intra prediction modes that are used for the associated texture picture. In another version, the depth of an intra-block can be set equal to a depth values that is obtained by a weighted average of the surrounding samples (or blocks), where the weighting factors can be determined based on the used intra prediction modes. In a further version, the depth for an intra-block can be obtained by setting the depth samples equal to a value that is given by a particular function of the surrounding intra samples (e.g., the average, the median, the maximum, the minimum). Other spatial prediction algorithms are also possible. The depth assignment for intra-coded blocks can also be done inside a single loop over the blocks in an image. That means, the blocks are processed in a particular order (e.g., the coding order), and for both disparity-compensated and intra blocks, the depth values are generated in this order (i.e., the depth assignment for intra-coded blocks doesn't need to wait until all disparity-compensated blocks are processed).

Temporal Prediction of the Base View Depth Map

In general, pictures of the base view contain motion-compensated blocks and intra coded blocks. The depth values for motion-compensated blocks are derived by motion-compensated prediction of the depth map estimate for the corresponding reference picture. If a block of the texture picture is coded using a single motion hypothesis, the depth samples for this block can be obtained by displacing the depth samples of the depth map estimate for the reference picture (given by the signaled reference index) by the transmitted (or inferred) motion vector. This motion compensation operation can be performed with the accuracy of the transmitted motion vectors (which is usually a sub-sample accuracy) or with sample- or block-accurate motion vectors. If the motion compensation is performed with sub-sample accuracy, an interpolation filter is applied for generating the samples at sub-sample positions. If the motion compensation is performed with sample or block accuracy, the transmitted motion vectors are rounded before they are used. If the block of the associated picture is coded with more than two motion hypothesis, one of the hypotheses can be selected for motion compensation of the depth maps, or all motion hypotheses are used by generating the final depth map estimate for the block as a weighted sum of the depth prediction signals for the individual motion hypotheses. Furthermore, the depth samples for a block of a given sizes can be set equal to a representing depth. This representing depth can be obtained by selecting a particular location inside the block and deriving the depth value for this location using motion compensation, or it can be obtained by defining a function of the motion-compensated depth values for this block. Such a function can be the average of the depth samples, or the median of the depth samples, or the minimum or maximum of the depth samples, or the depth sample value that occurs most often in the block.

Update of a Depth Map Using the Coded Motion and Disparity Parameters

As mentioned above, the depth map estimate for a picture can be updated after coding the picture. In the following, we describe some embodiments of such an update algorithm. Blocks of the picture are processed in a particular order (for example, the coding order) and for each block, the following applies:

-   -   If the block has been intra-coded (in the associated texture         picture), the depth sample values for this block can be derived         by spatial prediction using the samples of neighboring block.         Some examples for such a spatial prediction technique have been         described above. The depth sample values can also be obtained by         motion compensation using the motion parameters of a neighboring         block (see the description for motion-compensated blocks below).         It is sometime advantageous if the intra block are processed         after all motion- and disparity-compensated blocks are         processed, because then more neighboring are available and can         be used for spatial prediction of depth samples or motion         parameters.     -   Otherwise, if the block is coded using one or more disparity         vectors (disparity hypotheses), the depth samples are derived by         converting the disparity vectors to depth values. If only one         disparity vector (disparity hypothesis) is used for the block,         the depth value if given by the corresponding disparity vector.         If two or more disparity vectors are used for the block, one of         the disparity vectors can be selected for deriving the depth         value, or for each disparity vector a depth value can be derived         and the finally assigned depth value is obtained by applying a         function of the individually derived depth values. Possible         functions are, among others, the minimum or maximum of the         individual depth values, the median of the depth values, the         average of the depth values, or the depth values that occurs         most often.     -   Note that a block that is coded using a disparity vector may         additionally be associated with a temporal motion vector. In         this case, the temporal motion vector can be ignored. Or the         derived depth values can be combined with depth values that are         derived for temporal motion hypotheses (see below) in any         specific way (e.g., by averaging these two signals).     -   Otherwise, the block is coded using only temporal motion         hypotheses and the temporal motion hypotheses are used for         updating the depth samples for the block.

In a first embodiment of the invention, the depth map samples are derived by straightforward motion compensated prediction using the depth map estimates associated with the reference pictures for the current view. This motion compensation operation can be realized by any of the embodiments for temporal prediction of the base view depth map described above.

In a second embodiment of the invention, the depth map samples are not simply motion compensated, but instead a depth correction value is derived based on the motion vector coded for the current view and the motion vector coded for the corresponding block in the reference view and this depth correction value is added to the depth map estimated in order to obtain an updated depth map estimate. The advantage of such an approach is that depth changes between two instances can be considered.

Let d_(prd) be the current depth estimate for a sample or a block, let m_(curr) be the motion vector that is actually used for motion-compensation of the current block, and m_(ref) be the motion vector for the reference block in the reference view (the reference block is derived by using a disparity vector given by the depth estimate d_(prd) as described above). Furthermore, let v_(t−1) be the disparity vector in the reference access unit and let v_(t) be the disparity vector in the current access unit. Given the basic equation for the interrelationship between the motion and disparity vectors that we derived in the beginning of the description, m _(curr) +v _(t−1) −m _(ref) −v _(t)=0,

-   -   the current disparity vector can be set equal to         v _(t) =v _(t−1)+(m _(curr) −m _(ref)),     -   if we assume that the coded motion parameters and the disparity         in the reference picture are correct. The disparity vector can         be converted into a depth and vice versa. Hence, the current         depth can be expressed as         d=d _(t−1) +f _(vd) ⁻¹(m _(curr) −m _(ref)),

The depth d_(t−1) is the depth value given in the reference image, it can be accessed using the motion vector for the current block. It is also possible to replace the depth in the reference image with the current estimate for the depth d_(prd), since this depth has been derived using motion compensation from the depth in a reference image.

We showed the basic concept for obtaining an updated depth value using the motion vectors of the current and the reference block. This basic concept can be used in a variety of actual implementations. For example, if more than one motion vector is used for the current block and/or the reference block, a single motion vector can be selected or different depth values can be derived for the different motion vector and the final depth is obtained by using the average (or any other function) of the individually derived depth values. Furthermore, only those motion hypotheses in the current and the reference block should be considered that use the same reference access unit (or reference time instant, or reference picture order count, or reference index). If such motion hypotheses don't exist, the conventional motion compensation process described above can be used or the depth sample can be marked as not available and are later replaced by suitable post-processing steps. Furthermore, the new depth value can be derived based on a single sample for a block, or for all samples of a block, or for a selected subset of the samples of a block. When different depth values for different samples are derived, separate depth values can be assigned for different regions of the current block (e.g., for all 4×4 blocks inside the current block), or the different depth values are used for deriving a representing depth for the entire block, e.g., by using the average, the median, the minimum, the maximum value, or the depth values that occurs most often. The depth map update process can also be combined with some pre-processing steps. For example, not available depth values can be replaced by the depth values of neighboring samples or blocks.

Regarding the afore-outlined description of methods 1-3, it should be noted that these different alternatives of polishing up the motion or motion/disparity vector/parameter candidate list by adding respective information gained from a block, such as block 40 _(R) in the reference view, would also be advantageous if used with other types of determining the disparity vector used to identify the respective block 40 _(R) of the reference view. In accordance with this embodiment, the depth estimator 28 in the decoder of FIG. 1 would be optional, just as the depth estimator 84 in the encoder of FIG. 2 would be.

In particular, in accordance with the latter aspect, the above description of methods 1-3 also revealed an apparatus for reconstructing a multi-view signal into a multi-view data stream, the apparatus comprising a dependent-view reconstructor 26, which is configured to do the following in order to reconstruct the dependent-view 22. Reference is made to the schematic illustrations of the multi-view signal of FIGS. 1 and 4, in order to describe the functionality. In particular, the dependent-view reconstructor 26 derives, for a current block 50 _(C) of a current picture 32 t ₂(T) and the dependent view 22, a list of motion vector predictor candidates by firstly determining a disparity vector 102 for current block 50 _(C) representing a disparity between the current picture 32 t ₂(T) of the dependent view 22 and the current picture 32 t ₁(T) of the reference view 20 of the multi-view signal at block 50C. In order to do so, the dependent-view reconstructor 26 uses motion and disparity vectors associated with a previously decoded portion of the multi-view signal such as motion/disparity vectors of pictures 32 t 1(T) and 32 t 2(T−1). In the other embodiments outlined above, the estimated depth-map associated with the current picture 32 t ₁(T) of the reference view was used as a basis for determining the disparity vector 102, with the estimation and updating of the depth map estimate using the motion and disparity vectors of previously coded pictures of the dependent view as well as the reference view having been described above, and in this regard the above description shall be incorporated for the current embodiment as well, but in principle, other possibilities exist as well. For example, the dependent-view reconstructor 26 could spatially/temporally predict a disparity vector for the current block 50 _(C) and could use this predicted disparity vector as the disparity vector 102.

Then, the dependent-view reconstructor 26 determines block 40 _(R) within the current picture of the reference view using the determined disparity vector 102, and adds a motion vector to the list of motion vector predictor candidates, which depends on the motion vector associated with the determined block 40R, i.e. motion vector 42 _(R).

As described above, in deriving the list of motion vector predictor candidates, the dependent-view reconstructor could also be configured to spatially and/or temporally predict one or more further motion vectors from spatially and/or temporally neighboring blocks of the dependent view 22, i.e. blocks spatially and/or temporally neighboring current blocks 50 _(C). The one or more further motion vectors or a version derived therefrom would then be added to the list of motion vector predictor candidates by the dependent-view reconstructor 26.

The dependent-view reconstructor extracts, for block 50 c, index information specifying one of the list of motion vector predictor candidates from the multi-view data stream and, in order to be more specific, from the dependent-view portion 22 thereof. As it is assumed that the current block 50 _(C) is subject to motion-compensated prediction, i.e. is associated with a temporal prediction mode, the dependent-view reconstructor 26 reconstructs block 50 _(C) by performing a motion-compensated prediction of block 50 _(C) using a motion vector which is equal to, or at least depends on, the specified motion vector candidate, i.e. the one indexed or specified by the index information. The overhead associated with the enlarged list of motion predictor candidates is comparatively low compared to the gain in motion vector prediction quality resulting from the adding of the motion vector candidate 42 _(R) determined from the reference view.

As has also been described above, the motion information extracted by the dependent-view reconstructor 26 for the current block 50 _(C) need not be restricted to the index information. Rather, the dependent-view reconstructor 26 could further be configured to extract, for block 50 _(C), a motion vector difference in relation to the specified motion vector candidate and to perform the reconstruction of block 50 _(C) such that the used motion vector further depends on a sum of the motion vector difference and the specified motion vector candidate, i.e. the one specified by the index information out of the list of motion vector predictor candidates.

In the above, motion- and disparity-compensated prediction have been strictly distinguished. However, the difference between both may vanish if, for example, the same mode is used to signal both, with the difference between both merely being derivable from an index indexing the picture relative to which the motion/compensated prediction is to be performed. Then, the just-described functionality of the decoder dependent-view reconstructor could be rewritten by replacing “motion” with “motion/disparity” as there would be no difference. Naturally, the measures should be taken so that the vector candidate actually specified refers to the same type of previously coded picture, i.e. temporally preceding or in view direction preceding, or that the even the adding to the list is restricted conditionally performed accordingly.

According to the above-described method 1, the dependent-view reconstructor 26 is configured to extract for block 50 _(C), further a reference picture index specifying a reference picture of a list of reference pictures, comprising the current picture 32 t ₁(T) of the reference view 20 and the already decoded pictures 32 t ₂(t<T) of the dependent view 22, and the dependent-view reconstructor 26 may be configured to, with the reference pictures as one of the already decoded pictures of the dependent view 22, perform the motion-compensated prediction using the one already decoded picture of the dependent view as specified by the reference picture index as a reference, and if the reference picture is the current picture 32 t ₁(T) of the reference view, add the determined disparity vector 102 or a modified disparity vector derived from the determined disparity vector 102 to a list of disparity vector prediction candidates, extract index information specifying one of the list of disparity vector predictor candidates from the multi-view data stream and reconstruct block 50 _(C) by performing a disparity-compensated prediction of block 50 _(C) using a disparity vector which depends on the specified disparity vector candidate using the current picture 32 t ₁(T) of the reference view 20 as a reference. Again, the difference between motion-compensated and disparity-compensated prediction could be dissolved. The same prediction mode could be signaled for block 50 _(C). As to whether motion-compensated or disparity-compensated prediction is actually performed by the dependent-view reconstructor 26, would be defined by the reference picture index which indexes into a buffer or list of reference pictures containing both, temporal predecessors, i.e. previously decoded pictures of the dependent view, as well as view predecessors, i.e. previously decoded pictures of other views.

As became clear from method 2, the dependent-view reconstructor 26 could also be configured to perform the derivation of the list of motion vector predictor candidates via a list of motion/disparity vector predictor candidates being a list of motion/disparity parameter candidates each including a number of hypotheses and, per hypothesis, a motion/disparity motion vector and a reference index specifying a reference picture out of such a common list of reference pictures just-outlined. The dependent-view reconstructor may then be configured to add motion/disparity parameters to the list of motion/disparity parameter candidates which depend on motion/disparity parameters associated with a determined block 40 _(R), and to reconstruct block 50 _(C) by performing motion/disparity-compensated prediction on block 50C using motion/disparity parameters which depend on a motion/disparity parameter candidates specified by the index information. The motion parameters could, as described above, concurrently determine the number of hypotheses, and a reference index, and a motion/disparity vector difference per hypothesis. As has also been described above, the number of hypotheses could be determined beforehand such as by way of the type of the picture.

And as described in method 3, the dependent-view reconstructor may additionally be configured to additionally adopt the partitioning for block 50C from block 50R as far as the motion/disparity prediction is concerned.

The encoder of FIG. 2 would, in accordance with the latter aspect, be configured to act accordingly in encoding the multi-view signal into the multi-view data stream. In particular, the dependent-view reconstructor 26 would derive, for block 50 _(C), a list of motion vector predictor candidates in the same manner. That is, a disparity vector for block 50 _(C) representing a disparity between the current picture of the dependent view 22 and the current picture of the reference view 20 of the multi-view signal at the current picture of the dependent view 22 would be determined via motion and disparity vectors associated with a previously encoded portion of the multi-view signal. Then, a block 50 _(R) within the current picture of the reference view would be determined using the determined disparity vector, and a motion vector would be added to the list of motion vector predictor candidates, which depends on a motion vector associated with the determined block of the picture of the reference view. The dependent view reconstructor would insert, for block 50 _(C), index information specifying one of the list of motion vector predictor candidates, into the multi-view data stream, and encode the block 50 _(C) by performing a motion-compensated prediction of the block 50 _(C) using a motion vector which depends on the specified motion vector candidate.

Although some aspects have been described in the context of an apparatus, it is clear that these aspects also represent a description of the corresponding method, where a block or device corresponds to a method step or a feature of a method step. Analogously, aspects described in the context of a method step also represent a description of a corresponding block or item or feature of a corresponding apparatus. Some or all of the method steps may be executed by (or using) a hardware apparatus, like for example, a microprocessor, a programmable computer or an electronic circuit. In some embodiments, some one or more of the most important method steps may be executed by such an apparatus.

Depending on certain implementation requirements, embodiments of the invention can be implemented in hardware or in software. The implementation can be performed using a digital storage medium, for example a floppy disk, a DVD, a Blu-Ray, a CD, a ROM, a PROM, an EPROM, an EEPROM or a FLASH memory, having electronically readable control signals stored thereon, which cooperate (or are capable of cooperating) with a programmable computer system such that the respective method is performed. Therefore, the digital storage medium may be computer readable.

Some embodiments according to the invention comprise a data carrier having electronically readable control signals, which are capable of cooperating with a programmable computer system, such that one of the methods described herein is performed.

Generally, embodiments of the present invention can be implemented as a computer program product with a program code, the program code being operative for performing one of the methods when the computer program product runs on a computer. The program code may for example be stored on a machine readable carrier.

Other embodiments comprise the computer program for performing one of the methods described herein, stored on a machine readable carrier.

In other words, an embodiment of the inventive method is, therefore, a computer program having a program code for performing one of the methods described herein, when the computer program runs on a computer.

A further embodiment of the inventive methods is, therefore, a data carrier (or a digital storage medium, or a computer-readable medium) comprising, recorded thereon, the computer program for performing one of the methods described herein. The data carrier, the digital storage medium or the recorded medium are typically tangible and/or non-transitionary.

A further embodiment of the inventive method is, therefore, a data stream or a sequence of signals representing the computer program for performing one of the methods described herein. The data stream or the sequence of signals may for example be configured to be transferred via a data communication connection, for example via the Internet.

A further embodiment comprises a processing means, for example a computer, or a programmable logic device, configured to or adapted to perform one of the methods described herein.

A further embodiment comprises a computer having installed thereon the computer program for performing one of the methods described herein.

A further embodiment according to the invention comprises an apparatus or a system configured to transfer (for example, electronically or optically) a computer program for performing one of the methods described herein to a receiver. The receiver may, for example, be a computer, a mobile device, a memory device or the like. The apparatus or system may, for example, comprise a file server for transferring the computer program to the receiver.

In some embodiments, a programmable logic device (for example a field programmable gate array) may be used to perform some or all of the functionalities of the methods described herein. In some embodiments, a field programmable gate array may cooperate with a microprocessor in order to perform one of the methods described herein. Generally, the methods are advantageously performed by any hardware apparatus.

While this invention has been described in terms of several embodiments, there are alterations, permutations, and equivalents which fall within the scope of this invention. It should also be noted that there are many alternative ways of implementing the methods and compositions of the present invention. It is therefore intended that the following appended claims be interpreted as including all such alterations, permutations and equivalents as fall within the true spirit and scope of the present invention.

REFERENCES

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The invention claimed is:
 1. A method for reconstructing a multi-view signal coded in a data stream, comprising: processing a list of plurality of motion vector candidates associated with a coding block of a current picture in a dependent view of the multi-view signal, comprising: obtaining a disparity vector with respect to the coding block of the current picture in the dependent view, wherein the disparity vector represents a disparity between the current picture of the dependent view and a current picture of a reference view of the multi-view signal, identifying a corresponding block in the current picture of the reference view based on the disparity vector, estimating a first motion vector based on a second motion vector associated with the corresponding block in the current picture of the reference view, adding the first motion vector into the list of plurality of motion vector candidates, and extracting, from the data stream, index information that specifies at least one of the list of motion vector candidates to be used for motion-compensated prediction; and reconstructing the coding block in the current picture of the dependent view by performing the motion-compensated prediction based on the at least one of the list of motion vector candidates.
 2. The method of claim 1, wherein the step of obtaining the disparity vector comprises: obtaining motion data associated with the current picture of the reference view; applying the motion data associated with the current picture of the reference view to a depth map estimate of a previous picture of the reference view to generate a first estimated depth map for the current picture of the reference view; deriving a second estimated depth map for the current picture of the dependent view based on the estimated depth map for the current picture of the reference view; and determining the disparity vector based on the second estimated depth map for the current picture of the dependent view.
 3. The method of claim 2, wherein the disparity vector for the coding block in the dependent view is determined further based on at least one disparity vector associated with one or more previously decoded coding blocks of the multi-view signal.
 4. The method of claim 1, further comprising: extracting, from the data stream, a motion vector residual directed to the selected motion vector; obtaining a refined motion vector based on the selected motion vector and the motion vector residual; and performing the motion-compensated prediction to predict the coding block based on the refined motion vector.
 5. The method of claim 1, wherein the list of motion vector candidates include one or more of: a first estimated motion vector determined based on motion data associated with a spatial neighbor coding block in the current picture of the dependent view; a second estimated motion vector determined based on motion data associated with a temporal neighbor coding block in a previous picture of the dependent view; a first modified estimated motion vector derived by modifying the first estimated motion vector; and a second modified estimated motion vector derived by modifying the second estimated motion vector.
 6. An apparatus for reconstructing a multi-view signal coded in a data stream, comprising: a dependent view reconstructor configured for: processing a list of plurality of motion vector candidates associated with a coding block of a current picture in a dependent view of the multi-view signal, comprising: obtaining a disparity vector with respect to the coding block of the current picture in the dependent view, wherein the disparity vector represents a disparity between the current picture of the dependent view and a current picture of a reference view of the multi-view signal, identifying a corresponding block in the current picture of the reference view based on the disparity vector, estimating a first motion vector based on a second motion vector associated with the corresponding block in the current picture of the reference view, adding the first motion vector into the list of plurality of motion vector candidates, and extracting, from the data stream, index information that specifies at least one of the list of motion vector candidates to be used for motion-compensated prediction; and reconstructing the coding block in the current picture of the dependent view by performing the motion-compensated prediction based on the at least one of the list of motion vector candidates.
 7. The apparatus of claim 6, further comprising a depth estimator configured for: obtaining motion data associated with the current picture of the reference view; applying the motion data associated with the current picture of the reference view to a depth map estimate of a previous picture of the reference view to generate a first estimated depth map for the current picture of the reference view; deriving a second estimated depth map for the current picture of the dependent view based on the estimated depth map for the current picture of the reference view; and determining the disparity vector based on the second estimated depth map for the current picture of the dependent view.
 8. The apparatus of claim 7, wherein the disparity vector for the coding block in the dependent view is determined further based on at least one disparity vector associated with one or more previously decoded coding blocks of the multi-view signal.
 9. The apparatus of claim 6, wherein the dependent-view reconstructor is further configured for: extracting, from the data stream, a motion vector residual directed to the selected motion vector; obtaining a refined motion vector based on the selected motion vector and the motion vector residual; and performing the motion-compensated prediction to predict the coding block based on the refined motion vector.
 10. The apparatus of claim 6, wherein the list of motion vector candidates include one or more of: a first estimated motion vector determined based on motion data associated with a spatial neighbor coding block in the current picture of the dependent view; a second estimated motion vector determined based on motion data associated with a temporal neighbor coding block in a previous picture of the dependent view; a first modified estimated motion vector derived by modifying the first estimated motion vector; and a second modified estimated motion vector derived by modifying the second estimated motion vector.
 11. Machine readable non-transitory medium having data stored thereon for reconstructing a multi-view signal coded in a data stream, wherein the data, when read by a machine, cause the machine to at least perform: processing a list of plurality of motion vector candidates associated with a coding block of a current picture in a dependent view of the multi-view signal, comprising: obtaining a disparity vector with respect to the coding block of the current picture in the dependent view, wherein the disparity vector represents a disparity between the current picture of the dependent view and a current picture of a reference view of the multi-view signal, identifying a corresponding block in the current picture of the reference view based on the disparity vector, estimating a first motion vector based on a second motion vector associated with the corresponding block in the current picture of the reference view, adding the first motion vector into the list of plurality of motion vector candidates, and extracting, from the data stream, index information that specifies at least one of the list of motion vector candidates to be used for motion-compensated prediction; and reconstructing the coding block in the current picture of the dependent view by performing the motion-compensated prediction based on the at least one of the list of motion vector candidates.
 12. The machine readable non-transitory medium of claim 11, wherein the step of obtaining the disparity vector comprises: obtaining motion data associated with the current picture of the reference view; applying the motion data associated with the current picture of the reference view to a depth map estimate of a previous picture of the reference view to generate a first estimated depth map for the current picture of the reference view; deriving a second estimated depth map for the current picture of the dependent view based on the estimated depth map for the current picture of the reference view; and determining the disparity vector based on the second estimated depth map for the current picture of the dependent view.
 13. The machine readable non-transitory medium of claim 12, wherein the disparity vector for the coding block in the dependent view is determined further based on at least one disparity vector associated with one or more previously decoded coding blocks of the multi-view signal.
 14. The machine readable non-transitory medium of claim 11, wherein the data, when read by the machine, further cause the machine to perform: extracting, from the data stream, a motion vector residual directed to the selected motion vector; obtaining a refined motion vector based on the selected motion vector and the motion vector residual; and performing the motion-compensated prediction to predict the coding block based on the refined motion vector.
 15. The machine readable non-transitory medium of claim 11, wherein the list of motion vector candidates include one or more of: a first estimated motion vector determined based on motion data associated with a spatial neighbor coding block in the current picture of the dependent view; a second estimated motion vector determined based on motion data associated with a temporal neighbor coding block in a previous picture of the dependent view; a first modified estimated motion vector derived by modifying the first estimated motion vector; and a second modified estimated motion vector derived by modifying the second estimated motion vector.
 16. A method for encoding a multi-view signal into a data stream, comprising: processing a list of plurality of motion vector candidates associated with a coding block of a current picture in a dependent view of the multi-view signal, comprising: obtaining a disparity vector with respect to the coding block of the current picture in the dependent view, wherein the disparity vector represents a disparity between the current picture of the dependent view and a current picture of a reference view of the multi-view signal, identifying a corresponding block in the current picture of the reference view based on the disparity vector, estimating a first motion vector based on a second motion vector associated with the corresponding block in the current picture of the reference view, and adding the first motion vector into the list of plurality of motion vector candidates for the coding block, determining at least one of the list of motion vector candidates to be used for reconstructing the coding block in the current picture of the dependent view via motion-compensated prediction, and generating index information specifying the at least one of the list of motion vector candidates; and inserting, into the data stream, the index information.
 17. The method of claim 16, wherein the step of obtaining the disparity vector comprises: obtaining motion data associated with the current picture of the reference view; applying the motion data associated with the current picture of the reference view to a depth map estimate of a previous picture of the reference view to generate a first estimated depth map for the current picture of the reference view; deriving a second estimated depth map for the current picture of the dependent view based on the estimated depth map for the current picture of the reference view; and determining the disparity vector based on the second estimated depth map for the current picture of the dependent view.
 18. The method of claim 17, wherein the disparity vector for the coding block in the dependent view is determined further based on at least one disparity vector associated with one or more previously decoded coding blocks of the multi-view signal.
 19. The method of claim 16, further comprising: extracting, from the data stream, a motion vector residual directed to the selected motion vector; obtaining a refined motion vector based on the selected motion vector and the motion vector residual; and performing the motion-compensated prediction to predict the coding block based on the refined motion vector.
 20. The method of claim 16, wherein the list of motion vector candidates include one or more of: a first estimated motion vector determined based on motion data associated with a spatial neighbor coding block in the current picture of the dependent view; a second estimated motion vector determined based on motion data associated with a temporal neighbor coding block in a previous picture of the dependent view; a first modified estimated motion vector derived by modifying the first estimated motion vector; and a second modified estimated motion vector derived by modifying the second estimated motion vector.
 21. An apparatus for encoding a multi-view signal coded into a data stream, comprising: a dependent view encoder configured for: processing a list of plurality of motion vector candidates associated with a coding block of a current picture in a dependent view of the multi-view signal, comprising: obtaining a disparity vector with respect to the coding block of the current picture in the dependent view, wherein the disparity vector represents a disparity between the current picture of the dependent view and a current picture of a reference view of the multi-view signal, identifying a corresponding block in the current picture of the reference view based on the disparity vector, estimating a first motion vector based on a second motion vector associated with the corresponding block in the current picture of the reference view, adding the first motion vector into the list of plurality of motion vector candidates, determining at least one of the list of motion vector candidates to be used for reconstructing the coding block in the current picture of the dependent view via motion-compensated prediction, and generating index information specifying the at least one of the list of motion vector candidates; and inserting, into the data stream, the index information.
 22. The apparatus of claim 21, further comprising a depth estimator configured for estimating the disparity vector by: obtaining motion data associated with the current picture of the reference view; applying the motion data associated with the current picture of the reference view to a depth map estimate of a previous picture of the reference view to generate a first estimated depth map for the current picture of the reference view; deriving a second estimated depth map for the current picture of the dependent view based on the estimated depth map for the current picture of the reference view; and determining the disparity vector based on the second estimated depth map for the current picture of the dependent view.
 23. The apparatus of claim 22, wherein the disparity vector for the coding block in the dependent view is determined further based on at least one disparity vector associated with one or more previously decoded coding blocks of the multi-view signal.
 24. The apparatus of claim 21, wherein the dependent-view encoder is further configured for: extracting, from the data stream, a motion vector residual directed to the selected motion vector; obtaining a refined motion vector based on the selected motion vector and the motion vector residual; and performing the motion-compensated prediction to predict the coding block based on the refined motion vector.
 25. The apparatus of claim 21, wherein the list of motion vector candidates include one or more of: a first estimated motion vector determined based on motion data associated with a spatial neighbor coding block in the current picture of the dependent view; a second estimated motion vector determined based on motion data associated with a temporal neighbor coding block in a previous picture of the dependent view; a first modified estimated motion vector derived by modifying the first estimated motion vector; and a second modified estimated motion vector derived by modifying the second estimated motion vector.
 26. Machine readable non-transitory medium having data stored thereon for encoding a multi-view signal into a data stream, wherein the data, when read by a machine, cause the machine to perform the following: processing a list of plurality of motion vector candidates associated with a coding block of a current picture in a dependent view of the multi-view signal, comprising: obtaining a disparity vector with respect to the coding block of the current picture in the dependent view, wherein the disparity vector represents a disparity between the current picture of the dependent view and a current picture of a reference view of the multi-view signal, identifying a corresponding block in the current picture of the reference view based on the disparity vector, estimating a first motion vector based on a second motion vector associated with the corresponding block in the current picture of the reference view, adding the first motion vector into a list of plurality of motion vector candidates for the coding block, determining at least one of the list of motion vector candidates to be used for reconstructing the coding block in the current picture of the dependent view via motion-compensated prediction, and generating index information specifying the at least one of the list of motion vector candidates; and inserting, into the data stream, the index information.
 27. The machine readable non-transitory medium of claim 26, wherein the step of obtaining the disparity vector comprises: obtaining motion data associated with the current picture of the reference view; applying the motion data associated with the current picture of the reference view to a depth map estimate of a previous picture of the reference view to generate a first estimated depth map for the current picture of the reference view; deriving a second estimated depth map for the current picture of the dependent view based on the estimated depth map for the current picture of the reference view; and determining the disparity vector based on the second estimated depth map for the current picture of the dependent view.
 28. The machine readable non-transitory medium of claim 27, wherein the disparity vector for the coding block in the dependent view is determined further based on at least one disparity vector associated with one or more previously decoded coding blocks of the multi-view signal.
 29. The machine readable non-transitory medium of claim 26, wherein the data, when read by the machine, further cause the machine to perform: extracting, from the data stream, a motion vector residual directed to the selected motion vector; obtaining a refined motion vector based on the selected motion vector and the motion vector residual; and performing the motion-compensated prediction to predict the coding block based on the refined motion vector.
 30. The machine readable non-transitory medium of claim 26, wherein the list of motion vector candidates include one or more of: a first estimated motion vector determined based on motion data associated with a spatial neighbor coding block in the current picture of the dependent view; a second estimated motion vector determined based on motion data associated with a temporal neighbor coding block in a previous picture of the dependent view; a first modified estimated motion vector derived by modifying the first estimated motion vector; and a second modified estimated motion vector derived by modifying the second estimated motion vector. 